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Written by Varsha Saraogi on Friday, 14 June 2019. Posted in Interviews
Jocette Coote's friendship with F45 founder Rob Deutsch led to her balancing modelling with motherhood while spearheading two F45 franchises
First, a confession: I dislike gym cardio. And for many reasons – predictable routines, puffed up fitness aficionados grunting loudly and the huge mirrors which remind me of the numerous doughnuts I devoured through the week. So when I marched into boutique gym F45 at Ravenscourt Park for a group HIIT class, I was inundated with excitement as well as a little nervousness. After all, I was going to do the workout regime which prepared Hugh Jackman for becoming Wolverine.
Enter the studio and there are sledgehammers parked on one side while the rest of the space is taken up by rowing machines, stationary bikes, kettlebells, Swiss balls, TRX bands and free weights – just about every toy you can think of employed in an effort to make even the beefiest of gym addicts sore. Packed with more than 20 invigorated exercise enthusiasts, the Angry Bird workout begins.
While I did expect frenetic, high-intensity bouts of blackout-inducing drills, the fast-paced bootcamp-style class didn't have a single dull moment and had me breaking a sweat for 45 minutes. From the always-evolving list of exercises that make up the various pods including deadlifts, squats and pull-ups to the motivating trainers, this HIIT class is packed with everything you need. And there's no fear of being abandoned as the coaches also check on every client for the correct form by giving individual attention to all. But what actually set this gym apart is the clever use of wall-mounted monitors that guide you through every session. Clearly, this isn't the traditional bootcamp class I anticipated it to be.
All of this is to say that this intense 45 minutes of interval training puts your fitness to the test. I'm not sure if I passed it but I finished on my feet. Well, barely. As I gather strength to get up after the class, I'm greeted by model-turned-entrepreneur Jocette Coote who looks the picture of health. She is the franchisee for this site as well as the F45 in Farringdon.
Coote who regularly joins the class couldn't do so this time as she's busy enrolling and explaining the eight-week challenge which has just commenced to potential clients. This is proof the passion she harbours for the franchise as well as fitness goes beyond making money and she aims to encourage more people to work out. Her main goal as an F45 franchisee is to "change attitudes of people who have gym memberships but don't use it." And she believes keeping a tab on clients by making regular calls is one way to get them to be more frequent. "I don't know why the fitness industry is letting these people slip through their fingers – we should be making people fit but instead companies aren't following up [to] make sure they're happy," she argues. Additionally, classes must cater to various kinds of bodies and not just those wanting to get ripped. "A lot of women have avoided going to the gyms for a long time because they feel it's going to be mostly muscly people but we're not like that," she states.
Furthermore, she's determined to play her part in solving the ubiquitous obesity crisis through the F45 franchise. "This is a fitness club where we're educating people about how to eat well, how to exercise, how to sleep, how much water to drink," Coote declares. "People go on diet plans but they get bored and then go back to their old way of life which is why it never really works. And that's why the obesity crisis hasn't really been tackled because of these quick fix solutions."
Coote wasn't always this passionate about fitness and health. Her education was in classical arts and she played for an orchestra in Australia. She then got an opportunity to try her hand at modelling and never looked back. And for good reason as it entailed better finances and an immense amount of globetrotting. More than two decades of modelling also instilled the love for fitness she has today. "From diet to sleeping patterns to emotions, a model must be made of steel as fitness levels and stamina must be at elite levels at all times," she recalls. "There's nothing worse than – if you've ever been in a casting – to stand up in a line of 30 women in a G-string and a bra and you have to turn around and you're all compared. I don't think they would do castings like that these days that they used to do to us but that was a motivating factor initially. Now it's about supporting my children and just being healthy for my kids."
While Coote was always lean during her modelling days, she realised how different it is to actually being healthy. "I never really understood fitness, I just knew how to fit a certain dress size but that's very different to actually being fit," she says. "A lot of models didn't last in the industry because they probably didn't eat enough food. If you don't eat enough food, your skin doesn't look good and depression comes along. If you're not looking after all the mechanisms in your body, there's all sorts of horrible after effects." But Coote continues to model even today. "I think that's got a lot to do with the exercises that we do here," she says adding that it's her mission to educate more women about "being strong, not skinny." "And teaching women how to get the body they want the right way and not the wrong way. The wrong way would be to be thin and boney and you wouldn't be strong."
Despite her passion for improving people's health, she wasn't looking to head a gym franchise. In fact, when her close friend and the godfather to her children, Rob Deutsch, told her of his ambition to launch F45 in Australia, she didn't think it was the best idea. "We actually all laughed at him that he was giving up banking, giving up his life here [in the UK] to go back to Australia," she remembers. But after meeting his co-founder Luke Istomin, coupled with his passion for fitness, he saw a spike in his franchise and "F45 opened quicker than the McDonald's in Australia." And since its launch, Coote has seen the brand make all kinds of gains.
It was Deutsch who planted the idea when he asked Coote to become a franchisee. "I can't remember the first time he asked us to but we always had this thing of 'Don't be silly,'" she says. After giving it a little thought, she was convinced to give it a go. "I asked him the question 'Who has failed in Australia?' and he said there was only one gym out of 450 that failed and that's the first bell that rang in my head," she continues. "I thought, 'Okay, that's interesting, that's doable." And then Coote launched the F45 in Farringdon in 2017 which was also the second F45 studio to open in London and in that first week itself had more than 250 people walk through the door. "It's absolutely exploded and we couldn't be happier to be honest," she adds. She then opened the F45 in Ravenscourt Park a year later. She didn't look for any other gym franchise. "It wasn't about the gym," she says. "It's about friendship I guess. And it's about just seeing a franchise in its infancy grow."
As Coote embarked on her entrepreneurial journey, she faced a few challenges before establishing her sites. "So we had a bit of an uphill battle to try and explain to people what F45 was, why you should exercise, what HIIT training is, what this EPOC theory is," she says, which she did along with managing her children. "It was having a baby on one hip and cooking the meal and talking to someone about why this was going to work."
Having kids at the same time as launching the franchise meant Coote couldn't go to the F45 headquarters for the franchisee training. "I had children so I actually didn't get to do the induction but as I have a special relationship with the company, I guess I got the one-on-one training rather than the group training," she says. However, she found the franchise model to be incredibly simple to operate. "You turn the TVs on and you have the exercises all figured out for you, we have personal trainers that we hire, we train them up to deliver the best personal training that they can," she says. "It was pretty straightforward to be honest."
While the franchisee was content with the operation, Coote faced challenges with marketing as she was one of the first franchisees in the UK and establishing an international brand like F45 wasn't easy. This meant the material was less suited for British clientele. "They had all of their marketing for Australians, so all materials had Australian accents and Australian celebrities which didn't really interpret very well for this market at all initially," she remembers, noting that she had to use her own content. "I'm going to get in trouble for saying this but we just had to use our own marketing plans but we weren't supposed to. All of that's changed now but that was a struggle in the beginning." Even the language used to promote the brand had to be altered. "So we used to be quite structured where you could only use these people and buzzwords but now they realise that because we're becoming so global, every single market has a different requirement [and] different fitness words they want to use," she continues.
Coote continues to create marketing campaigns today, especially on social media to attract future customers. Given how well-populated her territories in London are, she mainly relies on word of mouth. "Social media still plays a big part in the fitness industry but the main thing is 100% the experience when clients come in here," she states. "[If] they have a good experience, they get their body transformation, they're happy [then] they talk to their work colleagues, family and friends [and] they bring people in. The word of mouth is grossly underestimated."
Another challenge Coote faced in the UK was finding the right sites which fit the requirements of the franchisor. "That's another problem we face in the UK with finding big enough sites with the correct zoning," she says. "You don't want to be sharing the wall with residents because gyms can make quite a lot of noise. You've got to find a certain square meterage, the right conditions, the right kind of neighbours and then you have to find the right demographic in the area as well. It's a lot of things like this that can make or break you." Given how tough it is to find sites in Blighty and then maintain them with sky-rocketing rent prices, the class fee is slightly higher than what it is in Australia.
Despite these challenges, Coote is determined to take the brand to new heights in the UK. With two sites already, Coote has one more in the pipeline which will be opening soon. "I just wanted to have one for each child," she says. "I have thought of the area but cannot say. We've sort of tentatively put money into the business structure but not into the actual physical building."
Coote notes that one of the main reasons F45 is gaining serious mass is the group classes it offers and believes people today undoubtedly prefer these classes as opposed to a solo gym session. "We've had a lot of people join because they're lonely, so it's a great place to meet people now," she says. "It's people trading out their pub lives and coming into the gym and sitting around and talking with people. The team training environment is extremely motivational."
Apart from making the environment in the studio more encouraging, Coote wants to change the way people perceive fitness and the words associated with it as well. "Why does the fitness industry use these big hardcore words like 'Gonna kill you, it's going to be tough murder' – all of these really hardcore words are alienating a lot of the market," she says. "I want to get the 65-year-olds in here. I do have a handful of older people and they didn't want to hear words like that. It's these things, words the fitness industry [has] planted in our heads, when [the] fitness journey shouldn't really be this hard."
Coote indeed has healthy living and fitness in her core and that's for inspiring her children. "I had children late, I had children in my forties, which is what a lot of people do now," she says. "But in doing that, you're robbing some years away from the time you have with your children, so you owe it to them to be as fit and healthy and try and live as [long] as you possibly can. And fitness is a way to do that." She also hopes to play tennis with her toddlers when they get to their twenties and looking at her F45 gym routine, there's no doubt about it.
Given that the brand has recently got a cash injection from Mark Wahlberg who hailed F45 as "the future of fitness," it doesn't take an expert to see how the firm is only set to scale further. And Coote is ambitious to ensure she gets more Britons to work out. "Watching people's faces light up when they hit their personal best, that's truly inspirational – it's a wonderful feeling," she concludes.
Varsha Saraogi
As feature writer and a recent MA Journalism graduate, Varsha has joined the Elite team to fuel her passion. Along with being immersed in the money making sector and ranting about women's rights, she will be hunting for news about everything business related. And burying her head in economic magazines. Follow her on twitter at @msvarshasaraogi for her mundane musings.
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LMNA Chapters
LMNA CHANNEL
Rendezvous 2021
Local Research Contest
Louisiana Maps
LMNA BLOG
LMNA Coffee Table
Charles Paxton, LMNA Communications Officer here with some items and links to articles that you might find interesting.
Transmission Risks: How Wearing Masks & Distancing Counts in The Fight Against Corona Virus
I think we probably all have some family members and friends who worry us by not heeding the Governor's instructions about wearing masks and keeping six feet clear of each other. Feel free to share this graphic if you want. It very clearly shows how we can effectively mitigate the social risks of transmitting Corona Virus. The original poster is from Japan, shared by my Environmental Education mentor, Prof. Steve Hesse. I simply swapped out some Japanese writing. The Japanese are very considerate about wearing masks to protect those around them. They don't do it for their own safety, but for others'. We'll beat this pandemic yet!
A Decade After Deepwater Horizon How is Gulf Wildlife Faring? BP's Penalties Funding Largest Ecosystem Restoration Effort in U.S. History.
Read ARTICLE in WILDOPENEYE
Poster child for deadly oil spills, The Deepwater Horizon disaster still resonates today. Eleven people lost their lives, and an estimated 200,000,000 gallons of crude oil were leaked into the Gulf of Mexico over an agonizing period of 87 days. The shores of the Gulf of Mexico have suffered hurricanes, systemic erosion and submersion of marshes from canals, deforestation of the protective chenieres, invasive Nutria rats and pollution. America's lost 2000 square miles of Gulf coastal land over the past 90 years. Could this next decade herald better times for the Gulf coast, it's wildlife and the people who depend upon a healthier environment? A new report by The National Wildlife Federation summarizes the latest information available about ten wildlife species that were affected by the "ecosystem-level injury to the northern Gulf of Mexico," as well as the restoration efforts underway — what constitutes the largest ecosystem restoration effort in U.S. History!
The Spice of Life: The Lowly Roly-Poly
Louisiana Master Naturalist Kimmie Paxton's amusing and enlightening article about "the parson's pig" may well be of interest! Part of her Spice of Life electronic journal series!
Can you spare $8 trillion? How Investments In Tropical Forest Protection and Curbing Wildlife Trade Can Pay-off In Zoonotic Disease Prevention
HIV, H5N1, Nipah, Ebola, Marburg, SARS, MERS and COVID-19 are all zoonotic diseases transmitted from wildlife to people, most have proved expensive in economic and personal terms, and while the filoviruses may be an ancient evil and the Coronavirus 19 a very new one, they all share the underlying cause of unusual proximity between people and wildlife. Habitat destruction and human incursion are common factors. If you've been wondering whether environmental conservation makes economic sense, here is an interesting article from Science Magazine's Policy Forum that shows not only that it does, but how it does, and that we may simply no longer be able to discount the value of environmental destruction in the big balance sheet of modern human civilization. The mathematics at a glance: US $17.7-26.9 billion can be invested to prevent tropical deforestation and limit wildlife trade, to yield savings of US $8.1-15.8 trillion worth of damage.
DOWNLOAD ARTICLE From SCIENCE MAGAZINE
Maps From Space!
 The Dataset: Global map of the Biodiversity Intactness Index, from Newbold et al. (2016) Science. Download from UK Natural History Museum Data Portal. UK Natural History Museum Data Portal Data usage licence: CC BY 4.0
Want to make a spatial map of the world or your own favorite bits? We can now, thanks to the UN's online Biodiversity Lab and the technical wizards at NASA. I made the map on the left that shows The Biodiversity Intactness Index (2016) which is the modeled average abundance of originally present species in a grid cell, as a percentage, relative to their abundance in an intact ecosystem.
Pretty cool, huh? There are up to 115 global data layers for research use in both terrestrial and marine mapping. Find out more about this amazing Global Information System and the free course that trains us in its use.
READ ARTICLE ON WILDOPENEYE
Micha Petty, Louisiana Master Naturalist and President of Louisiana Exotic Animal Rehabilitation Network addressing Louisiana Master Naturalists Northeast on the subject of Wildlife Rehabilitation at Union Parish Library August 28, 2018. LEARN fulfills a unique role in Env. Ed and wildlife rescue and rehabilitation.
Louisiana Exotic Animal Resource Network Launches Fundraiser
Have you heard of L.E.A.R.N.? This organization based in Shreveport rescues and rehabilitates many kinds of wildlife from native birds of prey and herps to escaped or unwanted exotic pets. Micha Petty is working hard on the front-lines of wildlife conservation, fighting tooth and nail to keep his rescue and environmental education center open.
DONATE TO L.E.A.R.N. on GOFUNDME
READ A KITE ON A STRING AND OTHER TALES OF REHABILITATION
Kelby Ouchley to receive Dormon Award
June 6, 2020; Monroe, La. – The Caroline Dormon Outstanding Louisiana Naturalist Award 2020 will be presented to Kelby Ouchley at a Zoom assembly June 14, 2020, at 3 p.m. The statewide Award is made annually by the Louisiana Master Naturalist Association. Ouchley was nominated for the award by the Northeast Chapter of LMNA.
Ouchley is well known throughout the region for his career raising awareness about the natural history of Louisiana and promoting conservation. He was the force behind getting Black Bayou Lake designated a National Wildlife Refuge. He is the author of six books and his weekly radio broadcast, Bayou Diversity, is ongoing.
The Louisiana Master Naturalist Association founded the Outstanding Louisiana Naturalist Award as a tribute to the legacy of Caroline Dormon and to recognize people who personify her commitment to conserving and appreciating the rich biodiversity of Louisiana.
Ouchley is the third recipient of the award. Previous recipients are Dr. Charles Allen, Pitkin, La., 2018 and Vernon Antoine Brou, Jr., Abita Springs, Louisiana, 2019.
The award will be presented by Bob Thomas, president of the Louisiana Master Naturalist Association, and Bette J. Kauffman, president of the Northeast Chapter of LMNA, at a Zoom assembly. Please pre-register for the event using the link below:
You are invited to a Zoom meeting. When: Jun 14, 2020 03:00 PM Central Time (US and Canada)
Register in advance for this meeting at:
https://us02web.zoom.us/meeting/register/tZMvdeCvrD8pG9f9mN1xntoOCNH1FcgMVHcB
Contact: Bette J. Kauffman, 318-372-8117,
bjkauffman@gmail.com
Learn To Communicate About Climate Change
Our Earth's Future
A free online course from the American Museum of Natural History about Our Earth's Future. See link at https://www.coursera.org/lecture/earth-climate-change/welcome-to-our-earths-future-6U7uT.
Our Earth's Future is about the science of climate change and how to talk about it. You will learn from scientists in the fields of climatology, oceanography, Earth science, and anthropology who study how climate change is affecting people, populations, and ways of life. Explore the multiple lines of evidence for the human-induced climate change that is happening today, and consider what that means for the future of our planet. At the end of this course you will be able to understand key scientific principles, identify and address misconceptions, and contribute confidently to conversations about climate change.
Instructor is Debra Tillinger, Ph.D.
Enroll for Free, starts Apr 23. 15,000+ people already enrolled. Suggested 1-3 hours per week.
Bio. Dr. Tillinger holds a Ph.D. in ocean and climate physics from Columbia University. She works at the American Museum of Natural History as an educator on climate change and at Marymount Manhtattan College as an adjunct professor of physics. Her current research is based at NASA/GISS and focuses on the effects of declining sea ice on global climate. In addition to formal science education, Dr. Tillinger also presents scientific information through the arts in character as "Dr. Mermaid."
Overview of course.
Week 1. Climate Change Is Happening: See It. (2 hours to complete),
4 videos (total 49 min), 4 readings, 1 quiz
Week 2. It All Comes Down to the Ocean. (1 hour)
Week 3. Climate Change is Happening: Model It. (1 hour)
Week 4. Living with Climate Change (1 hour).
"Earth School" launches to keep people connected to nature during social isolation.
TED-Ed, UNEP, and 30 other collaborators launch a free educational platform for environmental adventures available to teachers, parents, students, and curious global citizens
Nairobi, 22 April 2020 - In response to the COVID-19 crisis, an unprecedented coalition has come together to launch "Earth School," which provides free, high-quality educational content to help students, parents and teachers around the world who are currently at home. Initiated by the United Nations Environment Programme (UNEP) and TED-Ed, Earth School takes students on a 30-day "Adventure" through the natural world.
The curated Earth School content features videos, reading materials and activities — which will be translated into 10 languages — to help students gain an understanding of the environment while considering their role within it. This is the biggest online learning initiative in UNEP's history and is available for free on TED-Ed's website.
According to the UN Educational, Scientific and Cultural Organization (UNESCO), more than 1.5 billion learners are affected by COVID-19 school closures. The pandemic has caused a health, economic, and education crisis; in the age of physical and social constraints, there is a strong need for global science literacy.
That is why UNEP and TED-Ed — in coordination with 30 collaborators, including National Geographic, WWF and UNESCO — came together to launch Earth School in just over two weeks. Built for children and youth ages 5-18, it spans 30 school days that run between Earth Day and World Environment Day on June 5, which this year will take place under the banner of Time for Nature.
TED-Ed creates free, video-based lessons on everything from animals and climate change to underwater farms. It is the educational arm of TED, whose library of thousands of interactive lessons — built by a network of 500,000 educators from across the world — spans all ages and subjects.
Each Adventure has been carefully selected by a panel of expert practitioners and caters to different age groups. Each consists of a hands-on experiment and nature discovery. In addition to TED-Ed's own content, Earth School will feature videos from notable media organizations including National Geographic, PBS LearningMedia and the BBC with the goal of empowering participating students to be caretakers of our planet.
"Billions of children are currently out of school because of COVID-19. But learning cannot stop. COVID-19 has revealed how deeply interconnected all life on this planet is," said UNEP's Executive Director, Inger Andersen. "I am delighted that UNEP, along with TED-Ed and other collaborators, are launching Earth School. Learning about the natural world will be critical to building a better and sustainable future for all."
"These unprecedented times highlight just how important it is for young people to connect with the natural world and understand science," said Vicki Phillips, executive vice president and chief education officer at the National Geographic Society. "We're thrilled to join forces with trusted organizations like UNEP and TED-Ed to cultivate a spirit of exploration and build empathy for the Earth, no matter where students are the world — even if it's from inside their homes, from a window, or on a short walk in the neighborhood."
"Despite being confined to their homes, this project shows that students, parents and teachers throughout the world can still engage in science-based learning and adventures together. Earth School is a collaboration between so many talented educators and incredible partners from around the world, which is why we're proud and thrilled to see the initiative feeding the global curiosity of home-bound students, all of whom are the future environmental stewards of our planet. This platform is a gateway to some of the most inspiring lessons on nature and the environment, and each lesson comes with practical and fun activities that students can engage with and share," said Logan Smalley, founding director of TED's youth and education initiative, TED-Ed.
The lessons were curated by a team of environmental education experts including Kathleen Usher Ph.D, Jessie Oliver and Juliane Voss, who worked with over 100 contributors in creating Earth School. The initiative is in support of SDG 4.7 and the Decade of Delivery and will contribute towards the Global Education Coalition launched by UNESCO last month to convene governments, technology partners and leaders in the education field to keep pupils learning. As part of this coalition, UNEP will be exploring how this content can be adapted and shared with children who aren't able to access the Internet.
Collaborators who have agreed to support this initiative include: BBC Ideas, Basel, Rotterdam and Stockholm Conventions, Bill Nye the Science Guy, Conservation International, CEE, Earth Day Network, Earth Challenge 2020, Environment Online (ENO), GeSI, International Olympic Committee, IUCN, Institute for Planetary Security, Junior Achievement, Learning in Nature, Littlescribe, Minecraft, National Geographic Society, Ocean Wise, Only One, Royal Geographic Society, SciStarter, Sitra, TAT, TED-Ed, The Nature Conservancy, UN Convention on Biodiversity, UN SDSN / TRENDS, UN Technology Innovation Lab, UNCCD, UNDP, UNEP, UNESCO, UNFCCC, UN Food and Agriculture Organization, University of Pennsylvania, Vult Labs, World Association of Girl Guides and Girl Scouts (WAGGGS), World Organization of the Scout Movement (WOSM), Wild Immersion and WWF.
Notes for Teachers
About the UN Environment Programme
UNEP is the leading global voice on the environment. It provides leadership and encourages partnership in caring for the environment by inspiring, informing and enabling nations and peoples to improve their quality of life without compromising that of future generations.
About TED-Ed
TED-Ed is TED's youth and education initiative. TED-Ed's mission is to spark and celebrate the ideas of teachers and students around the world. Everything we do supports learning — from producing a growing library of original animated videos , to providing an international platform for teachers to create their own interactive lessons, to helping curious students around the globe bring TED to their schools and gain presentation literacy skills, to celebrating innovative leadership within TED-Ed's global network of over 500,000 teachers. TED-Ed has grown from an idea worth spreading into an award-winning education platform that serves millions of teachers and students around the
world every week.
Rendezvous 2020 postponed to April 2021 Due To Need For Social Distancing
Due to safety concerns associated with the risk of COVID-19 contagion at public meetings, the LMNA Board of Directors at an impromptu meeting held on March 17th, voted unanimously to postpone our Rendezvous 2020 meeting to April 9th-11th 2021.
As near as possible the event will simply roll-over to next year. Members who have already paid for their rooms can maintain their reservations if they wish, or if they wish a refund, they may email Janie to arrange that. Be advised that those of us who have reserved rooms and apply for a refund may not necessarily be able to get the same rooms next year.
In case of a price increase, any price difference can be made up on the door next year.
We are sorry for any disappointment that this announcement may cause among our membership and wish you all a safe period of social distancing until the threat passes.
Please follow the recommendations of Louisiana Governor vis a vis mitigating the risk of contracting and communicating the virus.
Best wishes to you all and we look forward to seeing you all again soon.
Crosby Arboretum SPRING PROGRAM CALENDAR
2020_spring_crosbyarboretumquarterly_program_schedule_vol_34.2_3-3-20_final.pdf
Plant lovers among us in Louisiana may be interested in this. Thank you, Dr. Allen for this info about Crosby Arboretum's SPRING PROGRAM SCHEDULE. Their Round Robin says:
"We are offering four pages jam-packed with programs and events this season! Come pay us a visit soon and see what's in bloom (currently the pink honeysuckle azaleas).
Please join us this weekend for a nature sketching program and gallery opening by Robin Veerkamp:
INTRODUCTION TO NATURE SKETCHING
Saturday, March 7, 1:00 to 2:00 p.m.
Learn the basics of nature sketching and how to get started in a fun and rewarding pastime in this introductory class with artist Robin Veerkamp. Members free, non-members $5. Call 601-799-2311. Gallery opening follows.
SPRING GALLERY EXHIBIT OPENING: DRAWINGS BY ROBIN VEERKAMP
Saturday, March 7, 2:00 to 3:00 p.m. On Display June 8 - August 31
Picayune fine artist Robin Veerkamp works in colored pencils and chalk pastels, and specializes in drawing architecture, plants, animals and landscapes from original photography. Much of her work has been inspired by the beauty of the Crosby Arboretum, where she worked for over a decade. Robin teaches nature sketching throughout the year at the Arboretum. The opening event is free to all. Light refreshments will be served.
Patricia R. Drackett
Director, The Crosby Arboretum, Mississippi State University
Assistant Extension Professor of Landscape Architecture
The Crosby Arboretum/MSU Extension Service
P.O. Box 1639, 370 Ridge Road, Picayune, MS 39466
Ph. (601) 799-2311 Ext. 102 Fax (601) 799-2372"
www.crosbyarboretum.msstate.edu
"Extending Knowledge. Changing lives."
Celebrating Our Explorers and Adventurers At Union Parish Library Exhibition for Black History Month 2020!
I greatly enjoyed the exhibition on African American Explorers and Adventurers past and present currently running at the Union Parish Library.
Kimmie Paxton and I filmed the presentation event on February 21 for a DVD that will be archived at the library for use by patrons and schools.
I had no idea how many African Americans have made and are still making such impact in their work outdoors!
The presentation began with Stephanie Herrmann's introduction and the shocking revelation that most school kids spend less time outdoors than prison inmates these days and includes a recollection of how kids enjoyed a local camping expedition!
"The path is not easy, the climbing is rugged and hard, but the glory at the end is worthwhile." —Matthew Henson, first person to trek to the North Pole
This movie was filmed at Union Parish Library on Friday, February 21st 2020. It includes the following sections:
Stephanie Herrmann, Library Director
Prayer of Blessing for Adventurers and Explorers by
Rev. Donald Dredd, of Fellowship Baptist Church/Simsboro
Hit the Bike Trails with Torrance Strong
Rev. Bobby Joe Douglas, Word Church/Bastrop-Grambling
Torrance Strong, Cyclist Advocate #GOTSTRONG it's more than just cycling, it's about improving the community transport environment and accessibility to all cyclists. This made me think, "Wow! Time to inflate the tires and hit the trails in the wildlife refuges!"
Hook, Line, and Sinker with Torica Whitty
Introduced by Verdell Ventroy of Delta Sigma Theta Sorority, Inc.
Torica Whitty, Professional Angler & Motorcycle Outdoor Enthusiast talks very eloquently about her experiences in the USAF and as a professional Angler, the opportunities and benefits of fishing for everyone, including girls and ladies.
Backwoods Biologist with Maury Bedford
Introduced by Rev. Samuel Elsworth of Zion Hill Baptist Church
Maury Bedford, U.S. Fish and Wildlife Refuge Manager of
D'Arbonne Refuge and Upper Ouachita Wildlife Refuge. It was really interesting to hear this mild-spoken gentleman Wildlife Biologist as he encourages a new intake of staff into the service.
Not So Cuddly Critters with Nova Clarke
Introduced by Cynthia Gatson, 21st Century Learning Coordinator
Nova Clarke, vivacious Environmental Educator at Black Bayou National Wildlife Refuge is also a Louisiana Master Naturalist Association Member in our Northeast group.
Wild Wild West with Layon Gray
Introduced by Rev. James Douglas, Mt. Pisgah Baptist Church,
Marion Layon Gray, Broadway Playwright/Director
"Cowboy" The Story of Bass Reeves
Bayou Blues with Pon Dixson
Introduced by Fred Carr, Union Parish Voter's League President
Pon Dixson, U.S. Fish and Wildlife Refuge Manager Musician/Custom-Guitar Artisan talked about his life as a hunter and his later service career and recommends young people consider a career in the U.S. Fish and Wildlife service.
Introduction to Adventurers and Explorers Exhibit by Nell Wayne, City of Farmerville Mayor's Office &
Jackie Hill, D.A.R.T. Director
Tour of the Exhibit was hosted by Marilyn Holly, Library Board Member
Special thanks also go to our community donors who provided items for the awesome exhibit:
North Louisiana Aviation Museum,
Kevin Adkins,
Union Parish Museum of History and Art,
Terri Booth,
Buckskin Billy,
Lake D'Arbonne State Park,
Richard Lowery (Excellent bird photographer and Nature writer),
Black Bayou Lake and D'Arbonne National Wildlife Refuges.
This is the low resolution version of our latest film celebrating 2020 Black History Month for Union Parish Library. It's over two hours long and the DVD cut will be more compact.
Library Director Stephanie Herrmann is a member of our LMNA in the Northeast Chapter and one of the most vocal advocates of adventure and exploration that I've ever met!
She runs the local Kayak Club, The Annual River Rat Challenge, made a Save Our Swamp Litter abatement programme and started a seed-bank amongst other things. Her goal in 2020 is to reduce stereotypes and barriers for African Americans in the outdoors by celebrating the lives and stories of explorers and adventurers throughout black history. Her exhibition allows us to step into the shoes of pioneers that climbed Mount Everest and explored wild and unforgiving landscapes. The courageous. The bold. The audacious!
They were farmers, hikers, naturalists, biologists, environmentalists, rangers, cowboys, stage coach drivers, fur traders, mountain men, farmers, aviators, soldiers, hunters, botanists, mountaineers, climbers, astronauts, guides, abolitionists, U.S. Marshals, spies, scouts, surveyors, zoologists, wilderness trekkers, astronomers, conquistadors, cyclists, backpackers, writers, poets, campers, settlers, and founders. This list was not just the past, but is rather just the beginning…
Why A Walk In The Woods Is Good For You
We recently learned that prison inmates in the US spend more time outdoors than most school kids! Nature Deficit Disorder can be avoided with a little planning. Here is a shareable PDF of my wife, Kimmie Paxton's research project for certification in our Louisiana Master Naturalist Northeast group. The pamphlet was based upon her tri-fold display that is currently in service at the Black Bayou Lake Visitors' Center to show people how they can benefit from getting out into the fresh air and how being out in the wild can help us feel better whether we are going to the park, deeper woods or to the beach.
Different environments have different qualities. I was most surprised to learn about the forest phytoncides that can help boost our immune response. I'd seen people jogging determinedly aound West Monroe's Restoration Park, but had no idea that they (and I) were being sprinkled by a confetti of beneficial phyto-pharmaceuticals in the process!
Apparently it's best to spend a couple of days 'forest bathing' to get a good dose! Spring camping, here we come!
healing_nature_brochure_draft_8.26-1.pdf
1/2/2020 1 Comment
Forthcoming Natural History Events 2020
There's plenty to look forward to this coming year. My thanks to Dr. Charles Allen for circulating his Louisiana Nature events list for 2020. To this list I'll add other events as I hear about them, so please check this page periodically, and if your event is pertinent and isn't listed, then please let us know about it.
January is Museum Month in the Twin Cities! Visit Monroe's local museums, including Black Bayou Lake NWR's visitor center, and ULM's Natural History Museum get your passport stamped at each, and be eligible for prize drawings! (Passports are available at all the museums. Visit them in any order.) https://www.monroe-westmonroe.org/monroemuseums
Jan 8 Louisiana State Horticultural Society meeting in Hammond https://www.louisianastatehorticulturesociety.com/
lshs_annual_conference_agenda_2020.docx
Jan 11 West Calcasieu Parish Field Trip by David Booth and Gulf Coast Bird Club (Saturday). *Meet at 8:00 AM at Love's Truck Stop in Vinton. We will bird GED Lake, Vinton Sewage Pond, Carl Nabors Farm, Deep Woods Cemetery, and Ellis Moss Road. Target species are diving ducks, sparrows, and open country birds. Bring drinks and snacks. Group will do a fast food lunch in Vinton or a late sit down lunch in Sulphur on return. Limit 12 participants. http://losbird.org/fieldtrips.htm
Jan 18 the Arbor Day Celebration and Friends of The Louisiana State Arboretum meeting north of Ville Platte. See the Friends' Newsletter below.
friends_newsletter_jan_2020.pdf
Jan 18 Master Garden Symposium West Monroe https://www.monroe-westmonroe.org/things-to-do-details.cfm?id=6417
Jan 24-26 LA Ornithological Society meeting in Shreveport http://losbird.org/
Jan 25 The New Orleans Botanical Garden and the Native Plant Initiative of GNO are pleased to present:
Morning Lecture with Thomas Rainer, co-author of Planting in a Post-Wild World 9 am - 11am $25
Learn how to create beautiful, lush, ecologically functional plantings for green infrastructure, public plantings, and residential gardens based on native plant communities. This lecture will focus on rebuilding biodiversity in New Orleans urban landscapes and gardens. Landscape architect Thomas Rainer will address the topic of Rebuilding Abundance in Urban Landscapes. The talk will discuss real world strategies for designing multi-layered, colorful, and resilient urban plantings. Learn tips about how to select plants for urban conditions, how to prepare soil, and how to reduce weed pressure. Both practical and inspiring, the talk will focus on an expanded vision of nature in the city. https://www.npi-gno.org/events/
Jan 25 Baton Rouge Hilltop Arboretum's Gardening Symposium Featuring Doug Tallamy, Linda (Buglady) Auld and Bill Fontenot. https://www.lsu.edu/hilltop/programs/adult/symposium.php
Feb 7-9 LNPS annual meeting Woodworth https://85ca4306-f6e4-4fbd-b4a6-62798a3773c3.filesusr.com/ugd/38d545_0c8293fec4b9499cba757eeb1a1ce479.pdf
March 24 thru May 28 Plant identification classes at Allen Acres. Classes will be Tues-Wed and Thurs and cost $300 for the complete class (3 days) or two day ($200) or one day ($100). Lunch is included and there's a choice of lodging, to be booked independently. Please see the form below.
plant_id_classes_2020.pdf
April 3-5 Annual BBBB Bogs, Birds, Butterflies, Baygalls tours plus a 50 year anniversary and a 75 year birthday celebration at Allen Acres, Pitkin (details soon)
April 17-19 Louisiana Master Naturalist Association Annual Rendezvous at Camp Hardtner, near Pollock , Louisiana. All members are welcome to join this three day event of environmental education, fellowship and service (see our dedicated Rendezvous Page) Places need to be booked in advance.
April 24-26 LA Ornithological Society Spring meeting in Shreveport http://losbird.org/
May 14-17 and May 21-24 National Bug-guide Gathering Spring Edition, Allen Acres. See attached info below.
bugguide_gathering_may_14-17_2020-1.pdf
In addition the check the area chapters' websites for their own events.
Welcome to LMNA Blog
11/21/2019 Tracey Allen is in the process of organizing a great selection of speakers for our 2020 Rendezvous which will be at Camp Hardtner near Pollock, Louisiana.
The information posted on our Rendezvous Page will be updated on an ongoing basis, so feel free to check in to see the latest information about our retreat.
LMNA News Blog
Welcome to the Louisiana Master Naturalist Association News Blog.

redpajama_set_name: RedPajamaCommonCrawl


text:
\subsection{Detailed Results}

\subsubsection{Goodness-of-fit}

We start by examining the goodness-of-fit of various methods on various datasets, since if a method fails to fit the data, it is unlikely to detect the true Granger causality between event types.
As shown in Figure~\ref{fig:barplot-nll}, \method attains smaller NLLs than all baselines on all datasets, suggesting that \method consistently has a better fit than all baselines. Notably, on all three synthetic datasets, the NLLs of \method nearly match those computed by the ground-truth models.
These results confirm the flexibility of \method in learning the various types of event interactions and temporal effects.

\begin{figure}[!tbp]
  \reducemargin
  \centering
  \subfloat[Excitation\xspace]{\includegraphics[width=0.33\columnwidth]{figures/mhp-1K-10-nll.pdf}}
  \subfloat[Inhibition\xspace]{\includegraphics[width=0.33\columnwidth]{figures/mscp-1K-10-nll.pdf}}
  \subfloat[Synergy\xspace]{\includegraphics[width=0.33\columnwidth]{figures/pgem-1K-10-nll.pdf}}

  \subfloat[IPTV\xspace]{\includegraphics[width=0.36\columnwidth]{figures/IPTV-nll.pdf}}
  \subfloat[MT\xspace]{\includegraphics[width=0.33\columnwidth]{figures/{MemeTracker-0.4M-100-nll}.pdf}}

  \caption{Hold-out NLLs of various methods, where horizontal lines denote the ground-truth NLLs. \method attains the best NLLs on all datasets.
  }

  \label{fig:barplot-nll}
\end{figure}

\mysubsubsection{Causality Discovery}

We now examined the performance of \method on Granger causality discovery, both quantitatively and qualitatively.

\myparagraph{Quantitative Analsyis.}

\begin{table*}[tbp]

  \centering
  \caption{Results for Granger causality discovery on the four datasets with ground-truth causality available. The best and the second best results on each dataset are emboldened and italicized, respectively.

  }

  \resizebox*{\textwidth}{!}{
  \input{tables/results_granger.tex}
  }
  \label{tab:granger-causality-results}

  \reducemargin
\end{table*}

Table~\ref{tab:granger-causality-results} shows values of AUC and Kendall's $\tau$ of various methods on the four datasets that have ground-truth causality. The results in the table support the following conclusions.

First, \method performs the best overall and is most robust to various types of event interactions. It not only significantly outperforms all baselines on three of the four datasets (i.e., Inhibition\xspace, Synergy\xspace, and MT\xspace), but also achieves a close-second on Excitation\xspace, in which events were generated by a Hawkes process, and \method is supposed to have a disadvantage relative to Hawkes process-based baselines.

Second, once the underlying data generation process violates the assumptions of Hawkes process and exhibits complex event interactions other than excitation, Hawkes process-based methods tend to perform poorly, as seen from Inhibition\xspace and Synergy\xspace.

Finally, despite both being NPP-based methods, RPPN performs significantly worse than \method on all datasets. We suspect that this underperformance is caused by two issues in RPPN's construction of the Granger causality statistics with the attention weights.
First, RPPN restricts all attention weights to be positive, thus cannot distinguish between excitative and inhibitive effects.
Second, attention mechanism may not correctly attribute the model's prediction to its inputs, as shown in several recent studies \citep{jain2019attention,Serrano2019}.

\myparagraph{Qualitative Analysis.}

Figure~\ref{fig:granger-causality-matrix-IPTV} shows the heat map for the Granger causality matrix of IPTV\xspace dataset estimated by \method.
Almost all diagonal entries have large positive values, indicating that users, on average, exhibit strong tendencies to watch the TV programs of the same category.
Several positive associations between different TV program categories are also observed, such as from military, laws, finance, and education to news, and from kids and music to drama.
These results agree with common sense and are consistent with the findings of an existing study with HSG \citep{xu2016learning}.
Our method also suggests several meaningful negative associations, including ads to drama and education to entertainment; such negative associations, however, can never be detected by models that only consider the excitations between events, such as HSG.

\added{Appendix~\ref{ap:subsec:qualitative-analysis-MT} provides a detailed analysis of the estimated Granger causality matrix for MT\xspace dataset.}

\begin{figure}[!tbp]

  \centering
  \includegraphics[width=0.95\linewidth]{figures/IPTV-score_mat.pdf}
  \caption{Visualization of the estimated Granger causality statistic matrices on IPTV\xspace \replaced{.}{ and MT\xspace (Figure~\ref{fig:granger-causality-matrix-MT-1} \&~\ref{fig:granger-causality-matrix-MT-2}). Better viewed on screen.}}
  \label{fig:granger-causality-matrix-IPTV}
\end{figure}

\mysubsubsection{Scalability}
\label{subsubsec:scalability}

Finally, we investigate the scalability of \method in computing the Granger causality statistic by Algorithm~\ref{alg:batching-scheme}. Figure~\ref{fig:batching-speedup} shows how much speedup Algorithm~\ref{alg:batching-scheme} achieves over a naive implementation with different sequence lengths and batch sizes.
The results demonstrate that with batch size and average sequence length both being relatively large (i.e., greater or equal to $16$ and $100$, respectively), our algorithm can achieve over \emph{three orders-of-magnitude speedup} relative to a native implementation.
Furthermore, the speedup scales almost linearly with sequence length and batch size when they do not exceed $150$ and $16$, respectively, which is consistent with our analysis in Section~\ref{subsec:computing-causality-statistic}. Beyond this regime, only a sublinear relationship between the speedup and batch size or sequence length is observed, which is because the GPU we tested on was reaching its maximum utilization.

\begin{figure}[!tbp]

  \centering
  \includegraphics[width=0.9\columnwidth]{figures/mhp-1K-10-speedup}
  \caption{The speedup achieved by Algorithm~\ref{alg:batching-scheme} relative to a naive implementation with different average sequence lengths and batch sizes.}
  \label{fig:batching-speedup}
\end{figure}

\section{Additional Related Work}

\paragraph{Event Sequence Modeling}

With the increasing availability of multi-type event sequences, there has been considerable interest in modeling such data for both prediction and inference.
The majority of prior research in this direction has been based on the theory of point processes \citep{Daley2003}, a particular class of stochastic processes that characterize the distribution of random points on the real line.
Notably, Hawkes process \citep{hawkes1971point,hawkes1971spectra}, a special class of point process, has been widely investigated, partly due to its ability to capture mutual excitation among events and its mathematical tractability.
However, Hawkes process assumes that past events can only independently and additively influence the occurrence of future events, and that influence can only be excitative; these inherent limitations have restricted its modeling flexibility and render it unable to capture complex event interaction in real-world data.

As such, other more flexible models have been proposed, including the \emph{piecewise-constant conditional intensity model} (PCIM) \citep{Gunawardana2011} and its variants \citep{Weiss2013,Bhattacharjya2018}, and more recently a class of models loosely referred to as \emph{neural point processes} (NPPs) \citep{du2016recurrent,xiao2017modeling,mei2017neuralhawkes,Xiao2019}. These models, particularly NPPs, generally enjoy better predictive performance than parametric point processes, since they use more expressive machine learning models (e.g., decision trees, random forests, or recurrent neural networks) to sequentially compute the conditional intensity until next event is generated. A significant weakness of these models, however, is that they are generally uninterpretable and thus unable to provide summary statistics for determining the Granger causality among event types.

\paragraph{Granger Causality Discovery}

In his seminal paper, \citet{Granger1969} first proposed the concept of Granger causality for time series data.
Many approaches have been proposed for uncovering Granger causality for multivariate time series, including the Hiemstra-Jones test \citep{Hiemstra1994} and its improved variant \citep{Diks2006}, Lasso-Granger method \citep{Arnold2007}, and approaches based on information-theoretic measures \citep{Hlavackova-Schindler2007}.
However, as these methods are designed for the synchronous multivariate time series, they are not directly applicable to asynchronous multi-type event sequence data, since otherwise one has to discretize the continuous observation window.

\citet{Didelez2008} first established the Granger causality for event types in event sequences under the framework of marked point processes.
Later, \citet{Eichler2017} shows that Granger causality for Hawkes processes is entirely encoded in the excitation kernel functions (also called impact function).
To our best knowledge, existing research for Granger causality discovery from event sequences appears to be limited to the case of Hawkes process \citep{Eichler2017,xu2016learning,achab2017uncovering}, possibly because of this direct link between the process parameterization and Granger causality.

\paragraph{Prediction Attribution for Black-Box Models}

Prediction attribution, the task of assigning to each input feature a score for representing the feature's contribution to model prediction, has been attracting considerable interest in the field due to its ability to provide insight into predictions made by black-box models such as neural networks.
While various approaches have been proposed, there are two prominent groups of approaches: perturbation-based and gradient-based approaches.
Perturbation approaches \citep{Zeiler2014} typically comprise, first, removing, masking, or altering a feature, and then measuring the attribution score of that feature by the change of the model's output. While perturbation-based methods are simple, intuitive, and applicable to almost all black-box models, the quality of the resultant scores is often sensitive to how the perturbation is performed. Moreover, as these methods scale linearly with the number of input features, they become computationally unaffordable for high-dimensional inputs.

In contrast, backpropagation-based methods construct the attribution scores based on the estimation of local gradients of the model around the input instance with backpropagation. The ordinary gradients, however, could suffer from a ``saturation'' problem for neural networks with activation functions that contain constant-valued regions (e.g., rectifier linear unit (ReLUs)); that is, the gradient coming into a ReLU during the backward pass is zero'd out if the input to the ReLU during the forward pass is in a constant region. One valid solution to this issue is to replace gradients with discrete gradients and use a modified form of backpropagation to compose discrete gradients into attributions, such as layer-wise relevance propagation (LRP) \citep{Bach2015} and DeepLIFT \citep{shrikumar2017learning}. Another solution, proposed by Integrated Gradient (IG) \citep{Sundararajan2017}, is to use the line integral of the gradients along the path from the input to a chosen baseline.
\citet{Sundararajan2017} show that IG satisfies many desirable properties, as detailed in Proposition~\ref{prop:IG-DeepLIFT-properties}.

It is worth mentioning that much existing work often uses the intermediate results, produced by certain intelligible neural network architecture, as the attribution scores for an input. A most notable example of such an idea is the use of attention weights induced by some attention mechanism as the importance of the input \citep{Bahdanau2015,Xu2015}.
Recently, however, there are growing concerns on the validity of attention weights being used as the explanation of neural networks \citep{jain2019attention,Serrano2019}. In particular, \citet{jain2019attention} show that across a variety of NLP tasks, the learned attention weights are frequently uncorrelated with feature importance produced by gradient-based prediction attribution methods, and random permutation of attention weights can nonetheless yield equivalent predictions.

\section{Additional Technical Details}
\label{ap-sec:techinical}

\subsection{Proof of Proposition~\ref{prop:IG-DeepLIFT-properties}}
\label{subsec:proof-IG-DeepLIFT-properties}

\begin{proof}
That both IG and DeepLIFT satisfy~\ref{P:linearity}--\ref{P:impl-invariance} has been established in \citep{Sundararajan2017}. \ref{P:fidelity-to-control} is straightforward from the definion of either method. Thus, we only prove that both methods satisfy batchability~\eqref{P:batchability} with $F(\mathbf{X}) \triangleq \sum_{i = 1}^n f(\mathbf{x}_i)$.

To prove that IG satisfies batchability, we first rewrite the $\mathrm{IG}(F, \mathbf{X}, \underline{\X})$ as follows:
\begin{align*}
 \mathrm{IG}(F, \mathbf{X}, \underline{\X}) &= (\mathbf{X} - \underline{\X}) \odot \int_{0}^1 \nabla_{\mathbf{X}} F \left[\underline{\X} + \alpha (\mathbf{X} - \underline{\X})\right] d\alpha \\
 &= (\mathbf{X} - \underline{\X}) \odot \int_{0}^1 \sum_{i = 1}^n \nabla_{\mathbf{X}} f \left[\underline{\x}_i + \alpha (\mathbf{x} - \underline{\x}_i)\right] d\alpha
 \\
 &= (\mathbf{X} - \underline{\X}) \odot \int_{0}^1 \sum_{i = 1}^n \lbrace\nabla_{\mathbf{x}_i} f \left[\underline{\x}_i + \alpha (\mathbf{x} - \underline{\x}_i)\right] \rbrace \mathbf{e}_i^T d\alpha
 \\
 &= (\mathbf{X} - \underline{\X}) \odot {\left[ \int_{0}^1 \nabla_{\mathbf{x}_i} f \left[\underline{\x}_i + \alpha (\mathbf{x} - \underline{\x}_i)\right] d\alpha \right]}_{i = 1, \ldots, m},
\end{align*}
where the second step is due to that summation and gradients are swapable, and the third step is because the gradients of different terms are separable.
Thus, we have
\begin{equation}
 {\left[\mathrm{IG}(F, \mathbf{X}, \underline{\X})\right]}_{:, i} = (\mathbf{x}_i - \underline{\x}_i) \odot \int_{0}^1 \nabla_{\mathbf{x}_i} f \left[\underline{\x}_i + \alpha (\mathbf{x} - \underline{\x}_i)\right] d\alpha = \mathrm{IG}(f, \mathbf{x}_i, \underline{\x}_i),
\end{equation}
which establishes the formula.

The proof of DeepLIFT satisfying batchability can be established in a similar way as IG.
The key part, shown in the Proposition 2 of \citep{Ancona2017}, is that the attribution scores produced by DeepLIFT for a neural-network-like function $f$, an input $\underline{\x}$, and a baseline $\underline{\x}$, i.e., $\mathrm{DeepLIFT}(f, \mathbf{x}, \underline{\x})$ can be viewed as the Hadamard product between $\mathbf{x} - \underline{\x}$ and a modified gradient of $f$ at all its internal nonlinear layers. Since the last layer of $F$ is a simple linear addition of all $f(\mathbf{x}_i)$'s, the modified gradient of $F$ for input $\mathbf{x}_i$ is the same as the one of $f$ for $\mathbf{x}_i$. Thus, we have
\begin{equation}
  {\left[\mathrm{DeepLIFT}(F, \mathbf{X}, \underline{\X})\right]}_{:, i} = \mathrm{DeepLIFT}(f, \mathbf{x}_i, \underline{\x}_i).
\end{equation}

\end{proof}

\subsection{Proof of Proposition~\ref{prop:shapley-properties}}
\label{ap:subsec:proof-shapley-properties}

We first briefly review Shapley values.
Suppose there is a team of $d$ players working together to earn a certain amount of value. The value that every coalition $U \subseteq [d]$ achieves is $v(U)$, where $v : 2^d \mapsto \mathbb{R}$ is a value function.
Shapley values, proposed by \citet{shapley1953value}, provide a well-motivated way to decide how the total earning $v([d])$ should be distributed among such $d$ players. Specifically, the Shapley value for each player $i \in [d]$ is defined as
\begin{equation}
 \phi_v(i) = \sum_{U \subseteq [d] \setminus \{i\}} \frac{(|U|! (d - |U| - 1)!)}{d!} \left[ v(U\cup \{i\}) - v(U) \right].
 \label{eq:shapley-def}
\end{equation}

For any target function $f \in \mathcal{F}_d$, input $\mathbf{x} \in \mathcal{X}$, and baseline $\underline{\x} \in \mathcal{X}$, we define a value function $v_{f, \mathbf{x}, \underline{\x}}(U) \triangleq f(\mathbf{x}_{U} \sqcup \mathbf{x}_{\bar{U}}) $ for any $U \in [d]$, where $\mathbf{x}_{U} \sqcup \mathbf{x}_{\bar{U}}$ is the spliced data point between $\mathbf{x}$ and $\underline{\x}$, defined in~\eqref{eq:spliced-data}.
Then the Shapley values $[\phi_{v_{f, \mathbf{x}, \underline{\x}}}(i)]_{i \in [d]}$ can be viewed as an attribution method that provides the attribute scores for any $f$, $\mathbf{x}$, and $\underline{\x}$.

Now we prove that this attribution method based on Shapley valeus satisfies all four axioms (\ref{P:linearity}--\ref{P:impl-invariance}) and the fidelity-to-control (\ref{P:fidelity-to-control}), as stated in Proposition~\ref{prop:shapley-properties}.

\begin{proof}
First, it is clear from the definition of Shapley values in~\eqref{eq:shapley-def} that $\phi_{v_{f, \mathbf{x}, \underline{\x}}}(\cdot)$ satisfies linearity~\eqref{P:linearity} and implementation variance~\eqref{P:impl-invariance}.
Since \citet{shapley1953value} shows that for any value function $v$, the Shapley values $\phi_v(\cdot)$ satisfies that
\begin{equation*}
 \phi_v([d]) - \phi_v(\emptyset) = \sum_{i = 1}^d \phi_v(i),
\end{equation*}
substituting our definition of the value function $\phi_{v_{f, \mathbf{x}, \underline{\x}}}(\cdot)$ into the above equation yields
\[
 f(\mathbf{x}) - f(\underline{\x}) = \sum_{i = 1}^d \phi_{v_{f, \mathbf{x}, \underline{\x}}}(i),
\]
which establishes the completeness \eqref{P:completeness}.
For any $i \in [d]$ and $U \subseteq [d] \setminus \{i\}$, we have
\[
 v_{f, \mathbf{x}, \underline{\x}}(U \cup \{i\}) - v_{f, \mathbf{x}, \underline{\x}}(U) = f(\mathbf{x}_{U \cup \{i\}} \sqcup \mathbf{x}_{\bar{U} \setminus\{i\} }) - f(\mathbf{x}_{U} \sqcup \mathbf{x}_{\bar{U}})
\]
Note that $\mathbf{x}_{U \cup \{i\}} \sqcup \mathbf{x}_{\bar{U} \setminus\{i\} }$ and $\mathbf{x}_{U} \sqcup \mathbf{x}_{\bar{U}}$ only potentially differ on the $i$-th dimension. If $f$ does not depend on the $i$-th dimension of its input or $x_i = \underline{x}_i$ (which implies $\mathbf{x}_{U \cup \{i\}} \sqcup \mathbf{x}_{\bar{U} \setminus\{i\} } = \mathbf{x}_{U} \sqcup \mathbf{x}_{\bar{U}}$), then $f(\mathbf{x}_{U \cup \{i\}} \sqcup \mathbf{x}_{\bar{U} \setminus\{i\} }) = f(\mathbf{x}_{U} \sqcup \mathbf{x}_{\bar{U}})$ and thereby $\phi_{v_{f, \mathbf{x}, \underline{\x}}}(i) = 0$. Thus, $\phi_{v_{f, \mathbf{x}, \underline{\x}}}(\cdot)$ satisfies null player~\eqref{P:null-player} and fidelity-to-control~\eqref{P:fidelity-to-control}.

\end{proof}

\subsection{Dyadic Gaussian Basis}
\label{ap:subsec:dyadic-gaussian-basis}

Inspired by the dyadic interval bases used by \citet{Bao2017}, we choose the basis functions $\{\psi_r(\cdot)\}_{r = 1}^R$ to be the densities for a Gaussian family $\{\mathcal{N}(\mu_r, \sigma_r^2) \}_{r = 1}^R$, which we term \emph{dyadic Gaussian basis}.
The means of dyadic Gaussian basis are given by
\begin{equation}
  \mu_r = \begin{cases}
    0, & r = 1, \\
    L / 2^{R - r},  & r = 2, \ldots, R,
  \end{cases}
\end{equation}
and the standard deviations by $\sigma_r = \max(\mu_r / 3, \mu_2 / 3)$ for $r \in [R]$.
This design of basis functions reflects a reasonable inductive bias that the CIFs should vary more smoothly as the time increases. As shown in Figure~\ref{fig:dyadic-normal-example} for an example of $L=100$ and $R=5$, the first a few bases, due to their small means and variances, capture the short-term effects, whereas the last several characterize the mid/long-term effects.

\begin{figure}[!htbp]
  \centering
  \includegraphics[width=0.6\columnwidth]{figures/basis_function-eps-converted-to.pdf}
  \caption{An example of dyadic Gaussian bases for $L = 100$ and $R = 5$.
  The first a few bases, due to their small means and variances, can capture the short-term effects, whereas the last several characterize the mid/long-term effects.
  }
  \label{fig:dyadic-normal-example}
\end{figure}

\subsection{Proof of Proposition~\ref{prop:intra-seq-batching}}
\label{ap:subsec:proof-intra-seq-batching}

\begin{proof}

We omit the index $s$ in this proof for brevity. First, we rewrite $\tilde{Y}_{k, k'}$ as
\begin{align*}
 \tilde{Y}_{k, k'}= & \sum_{i = 1}^n \sum_{j=1}^i \mathbbm{I}(k_j = k') A_j(f_k, \mathbf{x}_i, \underline{\x}_i) \\
 = & \sum_{j = 1}^n \mathbbm{I}(k_j = k') \left[ \sum_{i=j}^n A_j(f_k, \mathbf{x}_i, \underline{\x}_i) \right] \\
 = & \sum_{j = 1}^n \mathbbm{I}(k_j = k') \left[ \sum_{i=j}^n A_j(F_{k, i}, \mathbf{x}_n, \underline{\x}_n) \right],
\end{align*}
where in the step step, we replace $f$ with $F$.
Since $F_{k, i}$, i.e., $ \int_{t_i}^{t_{i + 1}} \lambda_k(t') dt $, does not depend on the events before the $i$-th event, with null player~\eqref{P:null-player}, we have $A_j(F_{k, i}, \mathbf{x}_n, \underline{\x}_n) = 0$ for any $j < i$, which further implies that
\[
 \tilde{Y}_{k, k'} = \sum_{j = 1}^n \mathbbm{I}(k_j = k') \left[ \sum_{i=1}^n A_j(F_{k, i}, \mathbf{x}_n, \underline{\x}_n) \right].
\]
With linearity~\eqref{P:linearity}, we have
\begin{equation*}
 \tilde{Y}_{k, k'} = \sum_{j = 1}^n \mathbbm{I}(k_j = k') A_j \left(\sum_{i=1}^n F_{k, i}, \mathbf{x}_n, \underline{\x}_n \right),
\end{equation*}
which establishes the formula.

\end{proof}

\section{Additional Experimental Details}

\subsection{The settings for synthetic and real-world datasets.}
\label{ap:subsec:datasets}

We describe below the setup and preprocessing details for the five datasets that we consider in this paper. The statistics of these datasets are summarized in Table~\ref{tab:dataset-statistics}.
\begin{itemize} [itemsep=3pt]

 \item \textbf{Excitation\xspace.}
 This dataset was generated by a multivariate Hawkes process, whose CIFs are of the form:
 \[
   \lambda^*_k(t) = \mu_k + \sum_{i : t_i < t } \alpha_{k, k'} \beta_{k, k'} \exp[- \beta_{k, k'} (t - t_i)].
 \]
 We set $S=1000$, $K=10$, $n_s \sim \mathrm{Poisson}(250)$, $\mu_k \sim \mathrm{Uniform}(0, 0.01)$, and $\beta_{k, k} \sim \mathrm{Exp}(0.05)$. To generate a sparse excitation weight matrix $ \mathbf{A} \triangleq [\alpha_{k, k'}]_{k, k' \in [K]}$, we first selected all its diagonal entries and $M = 16$ random  off-diagonal entries, then generated the values for these entries from $\mathrm{Uniform}(0, 1)$, and finally scaled the matrix to have a spectral radius of $0.8$.

 \item \textbf{Inhibition\xspace.}
 This dataset was generated by a multivariate self-correcting point process, whose CIFs take the form:
 \[
  \lambda^*_k(t) = \exp(\alpha_k t + \sum_{i: t_i < t} w_{k, k_i}).
 \]
 We chose $S = 1000$, $K = 10$, $n_s \sim \mathrm{Poisson}(250)$, and $\alpha_k \sim \mathrm{Uniform}(0, 0.05)$. To generated a sparse weight matrix $\mathbf{W} = [w_{k, k'}]_{k, k' \in [K]}$, we first selected all its diagonal entries and $M = 16$ random off-diagonal entries and further generated the values for these entries from $\mathrm{Uniform}(-0.5, 0)$.

 \item \textbf{Synergy\xspace.}
 This dataset was generated by a proximal graphical event model (PGEM) \citep{Bhattacharjya2018}. PGEM assumes that the CIF of an event type depends only on whether or not its parent event types (specified by a dependency graph) have occurred in the most recent history.
 We designed a local dependency structure that consists of five event types labeled as A--E. Among these event types,  type E is the outcome and can be excited by the occurrence of type A, B, or C; type A and B, only when both occurred in the most recent history, would incur a large synergistic effect on type E; type C has an isolated excitative effect on type E and does not interacts with other event types; and finally, type D does not have any excitative effect and is introduced to complicate the learning task.
 The dependency graph, together with the corresponding time windows and intensity tables, illustrated in Figure~\ref{fig:pgem-setting}.
 To add more complexity to this dataset,  we further replicated this local structure for another copy, leading to a total of $K=10$ event types. We generated $S = 1000$ event sequences with a maximum time span of $T = 1000$.

 \item \textbf{IPTV\xspace.} We obtained the dataset from\footnote{\url{https://github.com/HongtengXu/Hawkes-Process-Toolkit/tree/master/Data}}. We further normalized the timestamps into the days and splitted long event sequences so that the length of each sequence is smaller or equal to $1000$.

 \item \textbf{MT\xspace.} We downloaded the raw MemeTracker phrase data from\footnote{\url{https://www.memetracker.org/data.html\#raw}}. We filtered the phrase data that occurred from 2008-08-01 to 2008-09-30 and from the top-100 website domains. We further normalized the timestamps into hours and filtered out those event sequences (i.e., phrase cascades) whose lengths are not in between $3$ and $500$.

\end{itemize}

\begin{table}[!htbp]
  \centering
  \caption{Statistics for various datasets.}
  \input{tables/data_statistics}
  \label{tab:dataset-statistics}
 \end{table}

\begin{figure}[!htbp]
  \centering
  \includegraphics[width=0.7\textwidth]{figures/pgem.pdf}
  \caption{The dependency graph, time windows, and intensity tables for the PGEM used in generating the Synergy\xspace dataset.}
  \label{fig:pgem-setting}
\end{figure}

\subsection{Implementation Details and Hyperparameter Configurations for Various Methods}
\label{ap:subsec:method-config}

For \method, the $\mathrm{Enc}(\cdot)$ and the $\bm{\alpha}(\cdot)$ were implemented by a single-layer GRU and a two-layer fully connected network with skip connections, respectively.
The dimension of event type embeddings was fixed to $64$, and the number of hidden units for GRU was set to be $64$ for synthetic datasets and $128$ for real-world datasets.
The number of basis functions $R$ and the maximum mean $L$ were chosen by a rule of thumb such that $\mu_2$ and $\mu_R$ are of the same scale as the $50$th and the $99$th percentiles of the inter-event elapsed times, respectively.
The optimization was conducted by Adam with an initial learning rate of $0.001$.
A hold-out validation set consisting of $10\%$ of the sequences of the training set was used for model selection; the model snapshot that attains the smallest validation loss was chosen.
As events sequence lengths vary greatly on two real-world datasets, in constructing mini-batches for both training and inference, we adopted the bucketing technique to reduce the amount of wasted computation caused by padding.
Finally, the line integral of IG, defined in~\eqref{eq:ig-defn}, was approximated by $20$ steps for MT\xspace and $50$ steps for other datasets; a smaller number of steps, although may result in certain lose of accuracy, allows for a larger batch size and thus shorter execution time for attribution.

For the Hawkes process-based baselines---HExp, HSG, and NHPC---their implementation was provided by the package \texttt{tick} \citep{bacry2017tick}. The most relevant hyperparameters for each method were tuned by cross-validation.

As there is no publicly available codes for RPPN, we implemented it with our best effort. Its overall settings for architecture and optimization is similar to the ones for \method.

\subsection{Platform and Runtime}

All experiments were conducted on a server with a 16-core CPU, 512G memory, and two Quadro P5000 GPUs.
On the largest dataset, MT\xspace, the total runtime for \method was less than 3 hours, including both training and computing the Granger causality statistic.

\subsection{Qualitative Analysis on MT\xspace}
\label{ap:subsec:qualitative-analysis-MT}

Since there are too many event types in MT\xspace, instead of a heat map, we visualize the causality matrix as a graph and show in Figure~\ref{fig:granger-causality-matrix-MT-1} and Figure~\ref{fig:granger-causality-matrix-MT-2} the top-two communities of that graph, where the directed edges denote the estimated Granger causality between pairs of domains.\footnote{The graph visualization and community detection were performed using the software \texttt{Gephi}.}
In Figure~\ref{fig:granger-causality-matrix-MT-1}, the domain \texttt{news.google.com} centers in the middle and is pointed by many sites, which is unsurprising because Google News aggregates articles from other publishers and websites. Our method also correctly identifies other major ``information-consuming'' domains such as \texttt{bogleheads.org}, an active forum for investment-related Q\&A.
In Figure~\ref{fig:granger-causality-matrix-MT-2}, the then very popular social networking website \texttt{blog.myspace.com} sits in the center of the community.
Our method also identifies credible excitative relationships between the subdomains of \texttt{craigslist.org}, a mega-website that hosts classified, local advertisements.

\begin{figure*}[!tbp]

  \centering
  \subfloat[MT\xspace (Community 1)]{
  \includegraphics[width=0.45\textwidth]{figures/{MT-0.4M-100-graph-1}.png}
  \label{fig:granger-causality-matrix-MT-1}
  }
  \subfloat[MT\xspace (Community 2)]{
  \includegraphics[width=0.45\textwidth]{figures/{MT-0.4M-100-graph-2}.png}
  \label{fig:granger-causality-matrix-MT-2}
  }
  \caption{The top-two communities of the estimated Granger causality statistic matrices on MT\xspace (Figure~\ref{fig:granger-causality-matrix-MT-1} \&~\ref{fig:granger-causality-matrix-MT-2}). Better viewed on screen.}

  \label{fig:granger-causality-matrix}
\end{figure*}

\section{A Primer on Measure and Probability Theory}
\label{ap:sec:measure-theory}

In this section, we review some of the basic definitions of in measure theory, which may help the understanding of the definition of Granger causality for multivariate point processes. Most of the content in this section were adapted based on primarily based on the Chapter 1 of \citep{durrett2019probability} and the Appendix 3 of \citep{Daley2003},

Let $\Omega$ be a set of ``outcomes'' and $\mathcal{F}$ a nonempty collection of subsets of $\Omega$. The set $\mathcal{F}$ is \textbf{$\sigma$-algebra} of $\Omega$, if it is closed under complement and countable unions; that is,
\begin{enumerate}
  \item if $A \in \mathcal{F}$, then $ \Omega \setminus A \in \mathcal{F}$, and
  \item if $A_i \in \mathcal{F}$ is a countable sequence of sets, then $\cup_i A_i \in \mathcal{F}$.
\end{enumerate}
With these two conditions, it's easy to see that $\sigma$-algebra is also closed under arbitrary (possibly uncountable) intersections.
From this, it follows that given a nonempty set $\Omega$ and a collection of $\mathcal{A}$ of subsets of $\Omega$, there is a smallest $\sigma$-algebra containing $\mathcal{A}$; we denote such smallest $\sigma$-algebra by $\sigma(\mathcal{A})$.
One particular $\sigma$-algebra is of particular interst---\textbf{Borel $\sigma$-algebra}; that is, the smallest $\sigma$-algebra containing all open sets in $\mathbb{R}^d$, denoted by $\mathcal{R}^d$.
Specifically, let $\mathcal{S}_d$ be the empty set plus all sets of the form $(a_1, b_1] \times \cdots (a_d, b_d] \subset \mathbb{R}^d$, where $-\infty \leq a_i < b_i \leq \infty$, then $\mathcal{R}^d = \sigma(\mathcal{S}^d)$. The superscript $d$ is dropped when $d = 1$.

A pair $(\Omega, \mathcal{F})$, in which $\Omega$ is a set and $\mathcal{F}$ is a $\sigma$-algebra of $\Omega$, is called a \textbf{measurable space}. A \textbf{measure} defined on $(\Omega, \mathcal{F})$ is a nonnegative countably additive set function; that is a function $\mu: \mathcal{F} \mapsto \mathbb{R}$ with
\begin{enumerate}
  \item $\mu(A) \geq \mu(\emptyset) = 0$ for all $A \in \mathcal{F}$, and
  \item if $A_i \in \mathcal{F}$ is a countable sequence of disjoint sets, then
  \begin{equation*}
    \mu(\bigcup_i A_i) = \sum_i \mu(A_i )
  \end{equation*}
\end{enumerate}
If $\mu(\Omega) = 1$, we call such a $\mu$ a \textbf{probability measure}.
The triplet $(\Omega, \mathcal{F}, \mu)$ is called a \textbf{measure space}, and a \textbf{probability space} if $\mu$ is a probability measure.

Given a probability space $(\Omega, \mathcal{F}, \mu)$, a real-valued function $X$ defined on $\Omega$ is said to be a \textbf{random variable} if for every Borel set $B \in \mathcal{R}$ we have $X^{-1}(B) \triangleq \{\omega: X(\omega) \in B \} \in \mathcal{F}$; in another words, $X$ is \textbf{$\mathcal{F}$-measuable}.
A \textbf{stochastic process} is a collection of random variables $\{X_i\}_{i \in \mathcal{I}}$ defined on a common probability space and indexed by a \textbf{index set} $\mathcal{I}$. In most cases, the index set can be positive numbers $\mathbb{N}_+$, or real line $\mathbb{R}_+$.
A \textbf{filtration} is a sequence of $\sigma$-algebras, denoted by $\{\mathcal{F}_i\}_{i \in \mathcal{I}}$, if $\mathcal{F}_j \subseteq \mathcal{F}_i$ if $j \leq i$ and $i, j \in \mathcal{I}$.
Given a stochastic process $\{X_i\}_{i \in \mathcal{I}}$ defined on $(\Omega, \mathcal{F}, \mu)$, the \textbf{natural filtration} of $\mathcal{F}$ with respect to the process is given by
\begin{equation}
  \mathcal{H}_i \triangleq \sigma \left(\{ X_j^{-1}(B) | j \in \mathcal{I}, j \leq i, B \in \mathcal{R} \} \right).
  \label{eq:natural-filtration}
\end{equation}
It is in a sense that the simplest filtration filtration available for studying the given: all information concerning the process, and only that information, is avaiable in the natural filtration. Thus, the natural filtration $\mathcal{H}_i$ can be often be viewed as the ``\textbf{history}'' of the subprocess $\{X_j\}_{j \leq i, j \in I}$. Note that sometimes the definition in~\eqref{eq:natural-filtration} is simply written as $\mathcal{H}_i \triangleq \sigma \left( \{ X_j | j \in \mathcal{I}, j \leq i\} \right)$.

A \textbf{point process} $\{T_i\}_{i\geq 1}$ is a real-valued stochastic process indexed on $N_+$ such that $T_i \leq T_{i + 1}$ almost surely. Each random variable is generally viewed as the arrival timestamp of an event.
For each point process, one can define a continuously indexed stochastic process associated with it called \textbf{counting process}, as $N(t) \triangleq \sum_{i = 1}^{\infty} \mathbbm{1}( T_i \leq  t)$. From this definition, it is easily seen that every realization of a counting process is a c\`adl\`ag (i.e.\ right continuous with left limits) step function, and that a counting process $N(t)$ equivalently defines a point process, as one can recover the event timestamp by $T_i = \inf \{t \geq 0: N(t) = i \}$. Due to this equivalence, the phrases point process and counting process, as well as their notation, $\{T_i\}_{i \in \mathbb{N}_+}$ and $N(t)$, are often used interchangably in the literature.
A $K$-dimensional \textbf{multivariate point process (MPP)}  is a coupling of $K$ point/counting process $\mathbf{N}(t) = [N_1(t), N_2(t),\ldots, N_K(t)]$. A realization of a multivariate point process is a multi-type event sequence, $\{(t_i, k_i)\}_{i \in \mathbb{N}_+}$, where $t_i$ indicates the event timestmap of the $i$-th event, and the $k_i$ indicates which dimension the $i$-th event comes from (often interpreted as event type).

The most common way to define an MPP is through a set of \textbf{conditional intensity functions (CIFs)}, one for each event type.
Specifically, let $\mathcal{H}(t) \triangleq \sigma( \{N_k(s) | k \in [K], s < t\})$ for any $t$ be the natural filtration of MPP and let $\mathcal{H}(t-) \triangleq \lim_{s \uparrow t} \mathcal{H}(s)$ the CIF for event type $k$ is defined as the expected instantaneous event occurrence rate conditioned on natural filtration, i.e.,
\begin{equation*}
 \lambda^*_k(t) \triangleq \lim_{\Delta t \downarrow 0} \frac{\mathbb{E} [N_k(t + \Delta t) - N_k (t) | \mathcal{H}(t)]}{\Delta t},
\end{equation*}
where the use of the asterisk is a notational convention to emphasize that intensity $\lambda^*_k(t)$ must be $\mathcal{H}(t)$-measurable for every $t$.

Finally, for any $\mathcal{K} \subseteq [K]$, denote by $\mathcal{H}_{\mathcal{K}}(t)$ the natural filtration expanded by the sub-process ${\{N_k(t)\}}_{k \in \mathcal{K}}$, i.e., $\mathcal{H}_{\mathcal{K}}(t) = \sigma( \{N_k(s) | k \in \mathcal{K}, s < t\})$, and further write $\mathcal{H}_{-k}(t) = \mathcal{H}_{[K] \setminus \{k\}}(t)$ for any $k \in [K]$.  For a $K$-dimensional MPP, event type $k$ is \textbf{Granger non-causal} for event type $k'$ if $\lambda^*_{k'}(t)$ is $\mathcal{H}_{-k}(t)$-measurable for all $t$.
This definition amounts to saying that a type $k$ is Granger non-causal for another type $k'$ if, conditioned on the history of events other than type $k$, the future $\lambda^*_{k'}(t)$ does not depend on the historical events of type $k$ at any time. Otherwise, type $k$ is said to be \emph{Granger causal} for type $k$.

\section{#1}\vspace*{0ex}}
\newcommand{\mysubsection}[1]{\vspace*{0ex}\subsection{#1}}
\newcommand{\mysubsubsection}[1]{\vspace*{0ex}\subsubsection{#1}\vspace*{0ex}}

\begin{document}

\twocolumn[

\reducemargin
\icmltitle{\method: Learning Granger Causality from Event Sequences using Attribution Methods}

\begin{icmlauthorlist}
\icmlauthor{Wei Zhang}{uw}
\icmlauthor{Thomas Kobber Panum}{aau}
\icmlauthor{Somesh Jha}{uw,xp}
\icmlauthor{Prasad Chalasani}{xp}
\icmlauthor{David Page}{duke}
\end{icmlauthorlist}

\icmlaffiliation{uw}{Computer Scineces Department, University of Wisconsin-Madison, Madison, WI, USA.}
\icmlaffiliation{aau}{Department of Electronic Systems, Aalborg University, Aalborg, Denmark.}
\icmlaffiliation{xp}{XaiPient, Princeton, NJ, USA.}
\icmlaffiliation{duke}{Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.}

\icmlcorrespondingauthor{Wei Zhang}{zhangwei@cs.wisc.edu}

\icmlkeywords{Machine Learning, ICML}

\vskip 0.3in
]

\printAffiliationsAndNotice{}

\begin{abstract}
  \input{00abstract}
\end{abstract}

\mysection{Introduction}
\label{sec:intro}
\input{01introduction}

\mysection{Background}
\label{sec:background}
\input{02background}

\mysection{Proposed: \method}
\label{sec:method}
\input{03method}

\mysection{Experiments}
\label{sec:experiments}
\input{04experiment}

\mysection{Conclusion}
\label{sec:conclusion}
\input{06conclusion}

redpajama_set_name: RedPajamaArXiv


text:
Colleges / Polytechnic University of Puerto Rico
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Polytechnic University of Puerto Rico is a private, nonprofit school in the city of Hato Rey, PR. Polytechnic University of Puerto Rico was founded in 1966 and the school presently has around 4,252 students a year, which includes 3,687 undergrads. Polytechnic University of Puerto Rico provides housing for up to 104 students. Most students live in off campus housing.
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HONG KONG (REUTERS) - Vertex Holdings, the venture capital arm of Temasek Holdings, expects to raise two separate funds for investments in Israel and the United States in 2018 after deploying most of the capital of existing funds there, its chief executive said on Friday (May 26).
The funds will target a size of about US$150 million (S$207.6 million) each, the same size as the existing funds for those countries, Kee Lock Chua, group president and CEO of Vertex, told Reuters in an interview. "The funds will be about the same size, give or take 20 per cent," Mr Chua said on the sidelines of the China Private Equity Summit.
Besides the Israel and US funds, Vertex also has a US$250 million China-focused venture capital fund and another targeting India and South-east Asia with US$200 million, as well as a global healthcare fund. Temasek invests in each of the funds, which also take money from outside investors.
Cyber security will be a focus of the Israel fund, while the US fund will seek investments in enterprise and infrastructure-related software among other areas, Mr Chua said. In China, machine learning "is a big deal", he added.
Vertex, one of the first investors in ride-sharing firm Grab, expects to continue to focus on consumer internet and software sector in South-east Asia, a region that could see a pick-up in activity in coming years, Mr Chua said.
"China clearly is still very vibrant, very hot and a lot of people are very active in that sense," Mr Chua added. "South-east Asia in the next few years will get a lot more attention, especially because all the governments... have been deregulating some of the industries to be more flexible to not be an impediment to this growth. You'll see more things going on."


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How should the Vikings handle the starting LG position?
1. How should the Vikings handle the starting LG position?
I think we resign Compton and draft a middle rounder (3-4) for the LG position. I personally think that's the most likely scenario. Spend the higher draft pick pick at RG.
The Vikings should sign a free agent to start at LG. Then, if available, they should draft a guy that can compete this year and next year to take that free agent's starting job.
Roger Saffold is the first free agent I would target. If he doesn't make it to free agency look at Mark Glowinski and Billy Turner.
Sign Compton to come back as a swing backup. If the team thinks Nick Easton is healthy sign him to be the starting center.
Sadly, you are probably right but the question was what should they do. Not what do we think they will do. I would have answered differently if the question was what we think they'll do.
I think they will miss out on guards in free agency because they will not value them right so that will sign Compton or someone like him to start. Then they will not value guards correctly in the draft and they will draft the next Danny Isidora or David Yankey.
Afterwards, the only reasonable thing for Wilf to do will be to fire Rick Spielman. A new GM will result in Mike Zimmer being let go after the year.
As unpopular as it will be, I kind of think my answer is what I think we should do. Compton was serviceable. Keep him (or sign a similarly priced FA) and use a 3-4 on a LG and let them compete.
I would use a 1-2 on RG. I'm sure the team has confidence that Elflein will improve, so you take and athletic RG high so that you have 3 high level athletes at C, RG, RT. That will open up the stretch run, screen, and play action game.
I don't think we should spend 1st and 2nd on OL. Maybe we can sign more of a mid-tier FA than Compton to improve LG.
Why isn't Ramon Foster listed as the a potential available free agent? When giving the answer of what free agents I would target I only considered the players listed in the original post.
I would really like to see Donovan Smith from TB signed to play LG.
He played LT in TB, but projected as a guard coming out of college, he is still young (26), won't demand a massive contract, and has never missed a game.
I agree with most here. Add a veteran starting OG and draft one too. Best case would be getting Brandon Scherff here at RG and plugging a rookie in at LG.
Most likely case is Compton returns at LG with a rookie starting at RG.
I only added guys that were at the top of the payroll list and those guys that also fall in the target age range (25-27) of free agents that they typically go after. Foster didn't fall in either category, so he didn't make that list, but he's certainly an option, just like many other guys like Jermon Bushrod, Andy Levitre, Jonathan Cooper, and AJ Cann.
I don't bring back Compton. I follow up an early round OL with another OL sometime in rounds 2-4. Those two plus Easton (assuming fully recovered) and Isadora battle it out for both Guard spots. If a potential starting Guard can be found in FA (Glowinski, Cann) for a "reasonable" price I add them to the competition.
Re-sign Compton and Easton (health pending). Then find someone in the draft.
I'm tired of us having to rely on FA to get even a mediocre lineman with a huge price tag attached.
Get the position right in the draft. I say use the 2nd round pick and hopefully find that guy.
Quinton Spain is another good FA option to consider at OG. It looks like there are quite a few decent options set to hit FA this year. Hopefully some of them make it and then the Vikings get someone locked up. Currently it looks like it will be an excellant free agent class at the position.
Spain was benched at one point last year. That's alarming.
Trenton Brown - who knows if the Patriots will pay up for him, but kid has played great for them this year, is a possible star down the road.
Bobby Massie - probably will resign with Bears.
Jordan Mills - might not resign but probably will with Bills.
Nick Easton - Is a free agent for the Vikings, do we bring him back I have no idea.
AJ Cann - strong guard, might be reasonable cost.
So they have options but most likely it would be through the draft with the 1st or 2nd round pick, ideally the 1st rounder unless someone falls that is too hard to pass up. Guys in the later rounds who could be of great value would be guys like Trevon Tate, Donnell Greene or Dru Samia, Michael Dieter or Terronne Prescod. Now I have said already I would love to basically give that contract we have with Mike Remmers to someone like Trent Brown on New England, I would do that in a second. And regardless Remmers has to go without question.
Sad thing is with Eflein does one draft a center and move him to guard, they must have tried him there, I wonder if he is better because he did struggle at center this past year a little. If so guys like Ross Pierschbacher, Connor McGovern, Erik McCoy or later round Sam Mustipher would be of great interest. I say McCoy for sure in terms of his talent and upside and could be a 3rd or 5th round pick who knows, depends on how he works out. Regardless the OL should be #1 priority, just look at the Colts on TV in the playoffs right now, does not matter who the RB is when that OL blocks like that and protects like that. It is just an absolute need for any team that wants to get to the Playoffs and win.


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