37 Results

Tutorial
Mon 1:00 Representation Learning Without Labels
S. M. Ali Eslami, Irina Higgins, Danilo J. Rezende
Tutorial
Mon 5:00 Causal Reinforcement Learning
Elias Bareinboim
Poster
Tue 7:00 Full Law Identification in Graphical Models of Missing Data: Completeness Results
Razieh Nabi, Rohit Bhattacharya, Ilya Shpitser
Poster
Tue 7:00 Causal Strategic Linear Regression
Yonadav Shavit, Ben Edelman, Brian Axelrod
Poster
Tue 7:00 Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs
AmirEmad Ghassami, Alan Yang, Negar Kiyavash, Kun Zhang
Poster
Tue 8:00 Invariant Risk Minimization Games
Kartik Ahuja, Karthikeyan Shanmugam, Kush Varshney, Amit Dhurandhar
Poster
Tue 8:00 Efficient Identification in Linear Structural Causal Models with Auxiliary Cutsets
Daniel Kumor, Carlos Cinelli, Elias Bareinboim
Poster
Tue 9:00 Learning and Sampling of Atomic Interventions from Observations
Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Ashwin Maran, Vinodchandran N. Variyam
Poster
Tue 9:00 Robustness to Spurious Correlations via Human Annotations
Megha Srivastava, Tatsunori Hashimoto, Percy Liang
Poster
Tue 9:00 CAUSE: Learning Granger Causality from Event Sequences using Attribution Methods
Wei Zhang, Thomas Panum, Somesh Jha, PRASAD Chalasani, David Page
Poster
Tue 9:00 Designing Optimal Dynamic Treatment Regimes: A Causal Reinforcement Learning Approach
Junzhe Zhang
Poster
Tue 9:00 LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments
Ali Teshnizi, Saber Salehkaleybar, Negar Kiyavash
Poster
Tue 11:00 Causal Structure Discovery from Distributions Arising from Mixtures of DAGs
Basil Saeed, Snigdha Panigrahi, Caroline Uhler
Poster
Tue 13:00 Distinguishing Cause from Effect Using Quantiles: Bivariate Quantile Causal Discovery
Natasa Tagasovska, Valérie Chavez-Demoulin, Thibault Vatter
Poster
Tue 15:00 Invariant Causal Prediction for Block MDPs
Amy Zhang, Clare Lyle, Shagun Sodhani, Angelos Filos, Marta Kwiatkowska, Joelle Pineau, Yarin Gal, Doina Precup
Poster
Tue 15:00 Double Reinforcement Learning for Efficient and Robust Off-Policy Evaluation
Nathan Kallus, Masatoshi Uehara
Poster
Tue 18:00 Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models
Yuta Saito, Shota Yasui
Poster
Wed 5:00 Causal Effect Identifiability under Partial-Observability
Sanghack Lee, Elias Bareinboim
Poster
Wed 5:00 On Validation and Planning of An Optimal Decision Rule with Application in Healthcare Studies
Hengrui Cai, Wenbin Lu, Rui Song
Poster
Wed 5:00 Causal Modeling for Fairness In Dynamical Systems
Elliot Creager, David Madras, Toniann Pitassi, Richard Zemel
Poster
Wed 5:00 Efficient Intervention Design for Causal Discovery with Latents
Raghavendra Addanki, Shiva Kasiviswanathan, Andrew McGregor, Cameron Musco
Poster
Wed 8:00 Alleviating Privacy Attacks via Causal Learning
Shruti Tople, Amit Sharma, Aditya Nori
Poster
Wed 8:00 Efficient Policy Learning from Surrogate-Loss Classification Reductions
Andrew Bennett, Nathan Kallus
Poster
Wed 8:00 Approximating Stacked and Bidirectional Recurrent Architectures with the Delayed Recurrent Neural Network
Javier Turek, Shailee Jain, Vy Vo, Mihai Capotă, Alexander Huth, Theodore Willke
Poster
Wed 10:00 Causal Effect Estimation and Optimal Dose Suggestions in Mobile Health
Liangyu Zhu, Wenbin Lu, Rui Song
Poster
Wed 12:00 DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training
Nathan Kallus
Poster
Thu 6:00 Strategic Classification is Causal Modeling in Disguise
John Miller, Smitha Milli, Moritz Hardt
Poster
Thu 6:00 Performative Prediction
Juan Perdomo, Tijana Zrnic, Celestine Mendler-Dünner, Moritz Hardt
Poster
Thu 6:00 Estimation of Bounds on Potential Outcomes For Decision Making
Maggie Makar, Fredrik Johansson, John Guttag, David Sontag
Poster
Thu 6:00 Causal Inference using Gaussian Processes with Structured Latent Confounders
Sam Witty, Kenta Takatsu, David Jensen, Vikash Mansinghka
Poster
Thu 17:00 Cost-effectively Identifying Causal Effects When Only Response Variable is Observable
Tian-Zuo Wang, Xi-Zhu Wu, Sheng-Jun Huang, Zhi-Hua Zhou
Poster
Thu 18:00 Few-shot Domain Adaptation by Causal Mechanism Transfer
Takeshi Teshima, Issei Sato, Masashi Sugiyama
Workshop
Fri 1:00 5th ICML Workshop on Human Interpretability in Machine Learning (WHI)
Adrian Weller, Alice Xiang, Amit Dhurandhar, Been Kim, Dennis Wei, Kush Varshney, Umang Bhatt
Workshop
Fri 6:00 ICML 2020 Workshop on Computational Biology
Delasa Aghamirzaie, Alexander Anderson, Elham Azizi, Abdoulaye Baniré Diallo, Cassandra Burdziak, Jill Gallaher, Anshul Kundaje, Dana Pe'er, Sandhya Prabhakaran, Amine Remita, Mark Robertson-Tessi, Wesley Tansey, Julia Vogt, Yubin Xie
Workshop
Fri 12:40 Invited Talk: Feedback in Imitation Learning: Confusion on Causality and Covariate Shift (Arun Venkatraman & Sanjiban Choudhury)
Sanjiban Choudhury, Arun Venkatraman
Workshop
Sat 3:00 Inductive Biases, Invariances and Generalization in Reinforcement Learning
Anirudh Goyal, Rosemary Nan Ke, Jane Wang, Theo Weber, Fabio Viola, Bernhard Schölkopf, Stefan Bauer
Workshop
Sat 5:50 Bridge Between Perception and Reasoning: Graph Neural Networks & Beyond
Jian Tang, Le Song, Jure Leskovec, Renjie Liao, Yujia Li, Sanja Fidler, Richard Zemel, Russ Salakhutdinov