MD4SG

Meetup @ NeurIPS 2021

NeurIPS 2021, curated by MD4SG

Welcome to NeurIPS 2021, MD4SG-style! The schedule for this conference is quite large, so we've curated a list of programming relevant to the MD4SG community, whether for its speaker/organizer/author or topic. Note that all times are in Pacific Standard Time (PST) as is the timezone used by the NeurIPS conference. (Convert to your timezone.)

This MD4SG meetup at NeurIPS 2021 is organized by Jessie Finocchiaro, Corinna Hertweck, and Lily Xu from the MD4SG Community Engagement team.

Many of the events and talks below require a NeurIPS registration to access. All participants have read the NeurIPS 2021 Code of Conduct and agree to abide by it.

MD4SG @ NeurIPS Socials

We will have two organized MD4SG socials. These socials are open to all and do not require a NeurIPS registration.

These will take place on the MD4SG Discord on the #neurips2021 channel. The Discord channel will be open throughout the conference — we encourage you all to visit and discuss throughout the conference.

Time Event Location
December 13
12:00 PST (convert to your timezone)
MD4SG @ NeurIPS Social MD4SG Discord
December 14
00:00 PST (convert to your timezone)
MD4SG @ NeurIPS Social MD4SG Discord

Tutorials

Time Title Presenter
December 6 13:00 – 17:30 PST Beyond Fairness in Machine Learning Timnit Gebru, Emily Denton
December 6 05:00 – 07:20 PST A Journey Through the Opportunity of Low Resourced Natural Language Processing — An African Lens Vukosi Marivate, David Adelani

Invited Talks

Time Title Presenter
December 7
15:00–16:30 PST
The Banality of Scale: A Theory on the Limits of Modeling Bias and Fairness Frameworks for Social Justice (and other lessons from the Pandemic) Mary Gray
December 9
07:00–08:30 PST
A Conversation on Human and Machine Intelligence Daniel Kahneman
December 9
10:00–11:00 PST
How Copyright Shapes Your Datasets and What To Do About It Amanda Levendowski
December 9
15:00–16:30 PST
Gender, Allyship & Public Interest Technology Meredith Broussard

Socials

Time Title Presenter
December 7
18:00 – 19:00 PST
Latinx in AI Social Andres Munoz, Maria Luisa Santiago
December 9
05:00 – 07:00 PST
Queer in AI Claas Voelcker
December 9
11:00 – 12:00 PST
Women in AI Ignite Anoush Najarian
December 10
11:00 – 12:00 PST
Un-bookclub Algorithms of Oppression Anoush Najarian, Sindhuja Parimalarangan

Workshops

Time Title Presenter
December 13
05:00 – 12:10 PST
Machine Learning Meets Econometrics (MLECON) David Bruns-Smith, Arthur Gretton, Limor Gultchin, Niki Kilbertus, Krikamol Muandet, Evan Munro, Angela Zhou
December 13
06:00 – 17:30 PST
Algorithmic Fairness through the lens of causality and robustness Jessica Schrouff, Awa Dieng, Golnoosh Farnadi, Mark Kwegyir-Aggrey, Miriam Rateike
December 13
07:00 – 4:45 PST
Human Centered AI Michael Muller, Plamen P Angelov, Shion Guha, Marina Kogan, Gina Neff, Nuria Oliver, Manuel Rodriguez, Adrian Weller
December 13
09:00 – 10:00 PST
AI for Humatarian Assistance and Disaster Response Ritwik Gupta, Esther Rolf, Robin Murphy, Eric Heim
December 13
09:00 – 14:50 PST
Learning in the Presence of Strategic Behavior Omer Ben-Porat, Nika Haghtalab, Annie Liang, Yishay Mansour, David Parkes
December 14
Tackling Climate Change with Machine Learning Maria João Sousa, Hari Prasanna Das, Simone Fobi, Ján Drgoňa, Tegan Maharaj, Yoshua Bengio
December 14
Machine Learning in Public Health Rumi Chunara, Daniel Lizotte, Laura Rosella, Esra Suel, Marie Charpignon
December 14
05:00 – 15:00 PST
Bridging the Gap: from Machine Learning Research to Clinical Practice
December 14
05:00 – 14:10 PST
Ecological Theory of Reinforcement Learning: How Does Task Design Influence Agent Learning? Manfred Díaz, Hiroki Furuta, Elise van der Pol, Lisa Lee, Shixiang (Shane) Gu, Pablo Samuel Castro, Simon Du, Marc Bellemare, Sergey Levine
December 14
05:00 – 13:45 PST
Political Economy of Reinforcement Learning Systems Thomas Gilbert, Stuart J Russell, Tom O Zick, Aaron J Snoswell, Michael Dennis
December 14
05:00 – 17:00 PST
Learning Meaningful Representations of Life Elizabeth Wood, Adji Bousso Dieng, Aleksandrina Goeva, Anshul Kundaje, Barbara Engelhardt, Chang Liu, David Van Valen, Debora Marks, Edward Boyden, Eli N Weinstein, Lorin Crawford, Mor Nitzan, Romain Lopez, Tamara Broderick, Ray Jones, Wouter Boomsma, Yixin Wang
December 14
05:20 – 14:15 PST
Cooperative AI Natasha Jaques, Edward Hughes, Jakob Foerster, Noam Brown, Kalesha Bullard, Charlotte Smith
December 14
06:00 – 14:00 PST
Machine Learning for Development World (ML4D): Global Challenges Paula Rodriguez Diaz, Konstantin Klemmer, Sally Simone Fobi, Oluwafemi Azeez, Niveditha Kalavakonda, Aya Salama, Tejumade Afonja
December 14
06:05 – 15:30 PST
Workshop on Human and Machine Decisions Daniel Reichman, Joshua Peterson, Kiran Tomlinson, Annie Liang, Tom Griffiths

Affinity Workshops

Time Title Presenter
Queer in AI Workshop Claas Voelcker, Arjun Subramonian, Vishakha Agrawal, Luca Soldaini, Pan Xu, Pranav A, William Agnew, Juan Pajaro Velasquez, Yanan Long, Ashwin S, Mary Anne Smart, Patrick Feeney, Ruchira Ray
December 7
08:00 – 20:00 PST
LatinX in AI (LXAI) Research @ NeurIPS 2021 1 Maria Luisa Santiago, Andres Munoz, Laura Montoya, Karla Caballero, Isabel Metzger, Jose Gallego-Posada, Juan Banda, Gabriela Vega, Amanda Duarte
December 8
11:00 – 14:30 PST
Indigenous in AI Workshop Mason Grimshaw, Michael Running Wolf, Patrick Feeney

Papers

Papers co-authored by members of the MD4SG community.

Authors Title
David Liu, Mate Lengyel A universal probabilistic spike count model reveals ongoing modulation of neural variability
Alexandra Peste, Eugenia Iofinova, Adrian Vladu, Dan Alistarh AC/DC: Alternating Compressed/DeCompressed Training of Deep Neural Networks
Varun Gupta, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Chris Waites Adaptive Machine Unlearning
Priya Donti, Aayushya Agarwal, Neeraj Vijay Bedmutha, Larry Pileggi, J. Zico Kolter Adversarially robust learning for security-constrained optimal power flow
Nate Veldt, Austin Benson, Jon Kleinberg Approximate Decomposable Submodular Function Minimization for Cardinality-Based Components
Wei Tang, Chien-Ju Ho, Yang Liu Bandit Learning with Delayed Impact of Actions
Cristóbal Guzmán, Nishant Mehta, Ali Mortazavi Best-case lower bounds in online learning
Shengjia Zhao, Michael Kim, Roshni Sahoo, Tengyu Ma, Stefano Ermon Calibrating Predictions to Decisions: A Novel Approach to Multi-Class Calibration
Tian Gao, Shankar Subramanian, Debarun Bhattacharjya, Xiao Shou, Nicholas Mattei, Kristin P Bennett Causal Inference for Event Pairs in Multivariate Point Processes
Ulrich Aïvodji, Hiromi None Arai, Sébastien Gambs, Satoshi Hara Characterizing the risk of fairwashing
Julien Grand-Clément, Christian Kroer Conic Blackwell Algorithm: Parameter-Free Convex-Concave Saddle-Point Solving
Nikos Vlassis, Ashok Chandrashekar, Fernando Amat, Nathan Kallus Control Variates for Slate Off-Policy Evaluation
Denizalp Goktas, Amy Greenwald Convex-Concave Min-Max Stackelberg Games
Jamie Kang, Faidra Monachou, Moran Koren, Itai Ashlagi Counterbalancing Learning and Strategic Incentives in Allocation Markets
Ho Chit Siu, Jaime Peña, Edenna Chen, Yutai Zhou, Victor Lopez, Kyle Palko, Kimberlee Chang, Ross Allen Evaluation of Human-AI Teams for Learned and Rule-Based Agents in Hanabi
Thomas Spooner, Nelson Vadori, Sumitra Ganesh Factored Policy Gradients: Leveraging Structure for Efficient Learning in MOMDPs
Elisa Celis, Anay Mehrotra, Nisheeth Vishnoi Fair Classification with Adversarial Perturbations
Mohammad Mahdi Khalili, Xueru Zhang, Mahed Abroshan Fair Sequential Selection Using Supervised Learning Models
Bailey Flanigan, Greg Kehne, Ariel Procaccia Fair Sortition Made Transparent
Shahrzad Haddadan, Yue Zhuang, Cyrus Cousins, Eli Upfal Fast Doubly-Adaptive MCMC to Estimate the Gibbs Partition Function with Weak Mixing Time Bounds
Jonathan Bragg, Arman Cohan, Kyle Lo, Iz Beltagy FLEX: Unifying Evaluation for Few-Shot NLP
Frances Ding, Jean-Stanislas Denain, Jacob Steinhardt Grounding Representation Similarity Through Statistical Testing
Meena Jagadeesan, Alexander Wei, Yixin Wang, Michael Jordan, Jacob Steinhardt Learning Equilibria in Matching Markets from Bandit Feedback
Kai Wang, Sanket Shah, Haipeng Chen, Andrew Perrault, Finale Doshi-Velez, Milind Tambe Learning MDPs from Features: Predict-Then-Optimize for Sequential Decision Making by Reinforcement Learning
Sirui Li, Zhongxia Yan, Cathy Wu Learning to delegate for large-scale vehicle routing
Jaeho Lee, Jihoon Tack, Namhoon Lee, Jinwoo Shin Meta-Learning Sparse Implicit Neural Representations
Kate Donahue, Jon Kleinberg Optimality and Stability in Federated Learning: A Game-theoretic Approach
Aurelien Bibaut, Maria Dimakopoulou, Nathan Kallus, Antoine Chambaz, Mark van der Laan Post-Contextual-Bandit Inference
Neehar Peri, Michael Curry, Samuel Dooley, John P Dickerson PreferenceNet: Encoding Human Preferences in Auction Design with Deep Learning
Lingxiao Wang, Zhuoran Yang, Zhaoran Wang Provably Efficient Causal Reinforcement Learning with Confounded Observational Data
Walter Gerych, Tom Hartvigsen, Luke Buquicchio, Emmanuel Agu, Elke A. Rundensteiner Recurrent Bayesian Classifier Chains for Exact Multi-Label Classification
Roshni Sahoo, Shengjia Zhao, Alyssa Chen, Stefano Ermon Reliable Decisions with Threshold Calibration
Frances Ding, Moritz Hardt, John Miller, Ludwig Schmidt Retiring Adult: New Datasets for Fair Machine Learning
Jai Moondra, Hassan Mortagy, Swati Gupta Reusing Combinatorial Structure: Faster Iterative Projections over Submodular Base Polytopes
Aurelien Bibaut, Nathan Kallus, Maria Dimakopoulou, Antoine Chambaz, Mark van der Laan Risk Minimization from Adaptively Collected Data: Guarantees for Supervised and Policy Learning
Zeyu Shen, Lodewijk Gelauff, Ashish Goel, Aleksandra Korolova, Kamesh Munagala Robust Allocations with Diversity Constraints
Wenshuo Guo, Michael Jordan, Emmanouil Zampetakis Robust Learning of Optimal Auctions
Celestine Mendler-Dünner, Wenshuo Guo, Stephen Bates, Michael Jordan Test-time Collective Prediction
Sohini Upadhyay, Shalmali None Joshi, Himabindu Lakkaraju Towards Robust and Reliable Algorithmic Recourse
Virginie Do, Sam Corbett-Davies, Jamal Atif, Nicolas Usunier Two-sided fairness in rankings via Lorenz dominance
Jessie Finocchiaro, Rafael Frongillo, Bo Waggoner Unifying lower bounds on prediction dimension of convex surrogates
Ziwei Xu, Xudong Shen, Yongkang Wong, Mohan Kankanhalli Unsupervised Motion Representation Learning with Capsule Autoencoders