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Neurips 2020 Workshop Book NeurIPS 2020 Workshop book Schedule Highlights Generated Fri Dec 18, 2020 Workshop organizers make last-minute changes to their schedule. Download this document again to get the lastest changes, or use the NeurIPS mobile application. Dec. 10, 2020 None Topological Data Analysis and Beyond Rieck, Chazal, Krishnaswamy, Kwitt, Natesan Ramamurthy, Umeda, Wolf Dec. 11, 2020 None Privacy Preserving Machine Learning - PriML and PPML Joint Edition Balle, Bell, Bellet, Chaudhuri, Gascon, Honkela, Koskela, Meehan, Ohrimenko, Park, Raykova, Smart, Wang, Weller None Tackling Climate Change with ML Dao, Sherwin, Donti, Kuntz, Kaack, Yusuf, Rolnick, Nakalembe, Monteleoni, Bengio None Meta-Learning Wang, Vanschoren, Grant, Schwarz, Visin, Clune, Calandra None OPT2020: Optimization for Machine Learning Paquette, Schmidt, Stich, Gu, Takac None Advances and Opportunities: Machine Learning for Education Garg, Heffernan, Meyers None Differential Geometry meets Deep Learning (DiffGeo4DL) Bose, Mathieu, Le Lan, Chami, Sala, De Sa, Nickel, Ré, Hamilton None Workshop on Dataset Curation and Security Baracaldo Angel, Bisk, Blum, Curry, Dickerson, Goldblum, Goldstein, Li, Schwarzschild None Machine Learning for Health (ML4H): Advancing Healthcare for All Hyland, Schmaltz, Onu, Nosakhare, Alsentzer, Chen, McDermott, Roy, Akera, Kiyasseh, Falck, Adams, Bica, Bear Don't Walk IV, Sarkar, Pfohl, Beam, Beaulieu-Jones, Belgrave, Naumann None Learning Meaningful Representations of Life (LMRL.org) Wood, Marks, Jones, Dieng, Aspuru-Guzik, Kundaje, Engelhardt, Liu, Boyden, Lindorff-Larsen, Nitzan, Krishnaswamy, Boomsma, Wang, Van Valen, Ashenberg None First Workshop on Quantum Tensor Networks in Machine Learning Liu, Zhao, Biamonte, Caiafa, Liang, Cohen, Leichenauer None Human in the loop dialogue systems Hedayatnia, Goel, Oraby, See, Khatri, Boureau, Geramifard, Walker, Hakkani-Tur None The pre-registration experiment: an alternative publication model for machine learning research Bertinetto, Henriques, Albanie, Paganini, Varol None Differentiable computer vision, graphics, and physics in machine learning Jatavallabhula, Allen, Dean, Hansen, Song, Shkurti, Paull, Nowrouzezahrai, Tenenbaum None Causal Discovery and Causality-Inspired Machine Learning Huang, Magliacane, Zhang, Belgrave, Bareinboim, Malinsky, Richardson, Meek, Spirtes, Schölkopf None Self-Supervised Learning for Speech and Audio Processing Mohamed, Lee, Watanabe, Li, Sainath, Livescu None Machine Learning and the Physical Sciences Anandkumar, Cranmer, Ho, Prabhat, Zdeborová, Baydin, Carrasquilla, Dieng, Kashinath, Louppe, Nord, Paganini, Thais 2 None ML Competitions at the Grassroots (CiML 2020) Chklovski, Mendrik, Banifatemi, Stolovitzky None Resistance AI Workshop Kite, Tesfaldet, Abdurahman, Agnew, Creager, Foryciarz, Gontijo Lopes, Kalluri, Png, Sabin, Skoularidou, Vilarino, Wang, Kapoor, Carroll None Workshop on Deep Learning and Inverse Problems Heckel, Hand, Baraniuk, Zdeborová, Feizi None 3rd Robot Learning Workshop Itkina, Bewley, Calandra, Gilitschenski, PEREZ, Senanayake, Wulfmeier, Vanhoucke None Machine Learning for Autonomous Driving McAllister, Weng, Omeiza, Rhinehart, Yu, Ros, Koltun None Fair AI in Finance Kumar, Rudin, Paisley, Moulinier, Bruss, K., Tibbs, Olabiyi, Gandrabur, Vyetrenko, Compher None Object Representations for Learning and Reasoning Agnew, Assouel, Chang, Creswell, Kosoy, Rajeswaran, van Steenkiste None Crowd Science Workshop: Remoteness, Fairness, and Mechanisms as Challenges of Data Supply by Humans for Automation Baidakova, Casati, Drutsa, Ustalov None Competition Track Friday Escalante, Hofmann None ML Retrospectives, Surveys & Meta-Analyses (ML-RSA) Yadav, Pradhan, Dodge, Jaiswal, Henderson, Gupta, Lowe, Jessica Forde, Pineau None Deep Reinforcement Learning Abbeel, Finn, Pineau, Silver, Singh, Devin, Laskin, Lee, Rajendran, Veeriah None KR2ML - Knowledge Representation and Reasoning Meets Machine Learning Thost, Talamadupula, Srikumar, Zhang, Tenenbaum None BabyMind: How Babies Learn and How Machines Can Imitate Zhang, Marcus, Cangelosi, Knoeferle, Obermayer, Vernon, Yu None Machine Learning for Economic Policy Zheng, Trott, Liang, Morgenstern, Parkes, Haghtalab Dec. 12, 2020 None Algorithmic Fairness through the Lens of Causality and Interpretability Dieng, Schrouff, Kusner, Farnadi, Diaz None Medical Imaging Meets NeurIPS Teuwen, Dou, Glocker, Oguz, Feragen, Lombaert, Konukoglu, de Bruijne None Learning Meets Combinatorial Algorithms Vlastelica, Song, Ferber, Amos, Martius, Dilkina, Yue None Machine Learning for the Developing World (ML4D): Improving Resilience Afonja, Klemmer, Kalavakonda, Azeez, Salama, Rodriguez Diaz None Biological and Artificial Reinforcement Learning Chua, Behbahani, Lee, Zannone, Ponte Costa, Richards , Momennejad, Precup None I Can’t Believe It’s Not Better! Bridging the gap between theory and empiricism in probabilistic machine learning Forde, Ruiz, Fernandez Pradier, Schein, Doshi-Velez, Valera, Blei, Wallach None Machine Learning for Engineering Modeling, Simulation and Design 3 Beatson, Donti, Abdel-Rahman, Hoyer, Yu, Kolter, Adams None Machine Learning for Creativity and Design 4.0 Elliott, Dieleman, Roberts, White, Ippolito, Grimm, Tesfaldet, Azadi None Cooperative AI Graepel, Amodei, Conitzer, Dafoe, Hadfield, Horvitz, Kraus, Larson, Bachrach None Machine Learning for Molecules Hernández-Lobato, Kusner, Paige, Segler, Wei None Navigating the Broader Impacts of AI Research Ashurst, Campbell, Raji, Barocas, Russell None Beyond BackPropagation: Novel Ideas for Training Neural Architectures Malinowski, Swirszcz, Patraucean, Gori, Huang, Löwe, Choromanska None MLPH: Machine Learning in Public Health Chunara, Flaxman, Lizotte, Patel, Rosella None Wordplay: When Language Meets Games Ammanabrolu, Hausknecht, Yuan, Côté, Trischler, Mathewson, Urbanek, Weston, Riedl None Interpretable Inductive Biases and Physically Structured Learning Lutter, Terenin, Ho, Wang None AI for Earth Sciences Mukkavilli, Hansen, Dudek, Beucler, Kochanski, Mudigonda, Kashinath, McGovern, Miller, Frischmann, Gentine, Dudek, Courville, Kammen, Kumar None Machine Learning for Mobile Health Futoma, Dempsey, Heller, Ma, Foti, Njifon, Zhang, Shi None Talking to Strangers: Zero-Shot Emergent Communication Ossenkopf, Filos, Gupta, Noukhovitch, Lazaridou, Foerster, Bullard, Chaabouni, Kharitonov, Dessì None Shared Visual Representations in Human and Machine Intelligence (SVRHM) Deza, Peterson, Murty, Griffiths None Competition Track Saturday Escalante, Hofmann None Machine Learning for Structural Biology Townshend, Eismann, Dror, Zhong, Anand, Ingraham, Boomsma, Ovchinnikov, Rao, Greisen, Kolodny, Berger None Second Workshop on AI for Humanitarian Assistance and Disaster Response Gupta, Murphy, Heim, Wang, Goodman, Patel, Bilinski, Nemni None Consequential Decisions in Dynamic Environments Kilbertus, Zhou, Wilson, Miller, Hu, Liu, Kallus, Mitchell None HAMLETS: Human And Model in the Loop Evaluation and Training Strategies Kaushik, Paranjape, Arabshahi, Elazar, Nie, Bartolo, Kirichenko, Saito Stenetorp, Bansal, Lipton, Kiela None International Workshop on Scalability, Privacy, and Security in Federated Learning (SpicyFL 2020) Li, Dou, Talwalkar, Li, Wang, Wang None Workshop on Computer Assisted Programming (CAP) Odena, Sutton, Polikarpova, Tenenbaum, Solar-Lezama, Dillig None The Challenges of Real World Reinforcement Learning Mankowitz, Dulac-Arnold, Mannor, Gottesman, Nagabandi, Precup, Mann, Dulac-Arnold None Self-Supervised Learning -- Theory and Practice 4 Xie, Zhang, Agrawal, Misra, Rudin, Mohamed, Yuan, Zoph, van der Maaten, Yang, Xing None Machine Learning for Systems Goldie, Mirhoseini, Raiman, Maas, XU NoneOffline Reinforcement Learning Kumar, Agarwal, Tucker, Li, Precup, Kumar None Deep Learning through Information Geometry Chaudhari, Alemi, Jog, Mehta, Nielsen, Soatto, Ver Steeg 5 Dec. 10, 2020 Dec. 10, 2020 Schedule N/A Gather.Town (for poster sessions) Topological Data Analysis and Beyond N/A Rocket.Chat (for asking questions to panellists) Bastian Rieck, Frederic Chazal, Smita Krishnaswamy, N/A Slack (for asking questions to Roland Kwitt, Karthi Natesan Ramamurthy, Yuhei Umeda, Guy Wolf panellists) 11:00 Opening Remarks Chazal, Thu Dec 10, 23:00 PM PM Krishnaswamy, Kwitt, Natesan Ramamurthy, Rieck, Umeda, Wolf The last decade saw an enormous boost in the 11:15 Keynote: Kathryn Hess: Topological field of computational topology: methods and PM Insights in Neuroscience Hess concepts from algebraic and differential topology, 11:45 Invited Talk: Vidit Nanda: Singularity formerly confined to the realm of pure PM Detection in Data Nanda mathematics, have demonstrated their utility in 12:00 Invited Talk: Yuzuru Yamakage: numerous areas such as computational biology, AM Industrial Application of TDA-ML personalised medicine, materials science, and technology: Achievement so far and time-dependent data analysis, to name a few. expectations of future Yamakage 12:15 Invited Talk: Katharine Turner Turner The newly-emerging domain comprising AM topology-based techniques is often referred to as topological data analysis (TDA). Next to their 12:30 Invited Talk: Manohar Kaul: Solving applications in the aforementioned areas, TDA AM Partial Assignment Problems using methods have also proven to be effective in Random Simplicial Complexes Kaul supporting, enhancing, and augmenting both 12:45 Invited Talk: Yasuaki Hiraoka: classical machine learning and deep learning AM Characterizing Rare Events in models. Persistent Homology Hiraoka 01:00 Invited Talk: Serguei Barannikov: We believe
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