Schedule

Thursday, June 23rd in Empire Room (Marriott)

8:40

Opening Remarks
Jacob Steinhardt
 9:00   Session 1: Counterfactual Reasoning
9:00

Invited Talk: Causal Reasoning and Learning Systems.
Leon Bottou
 9:30   Contributed Talk: Bounding and Minimizing Counterfactual Error.
 Uri Shalit, Fredrik Johansson, David Sontag.
9:45

9:45-9:48


9:48-9:51


9:51-9:54


9:54-9:57


9:57-10:00

Poster spotlights 1

Robust Stochastic Optimization: Learning the Tails.
John C. Duchi, Hongseok Namkoong.

Data Poisoning Attacks for Factorization Based Collaborative Filtering.
Bo Li, Yining Wang, Aarti Singh, Yevgeniy Vorobeychik.

Debugging Machine Learning Models.
Gabriel Cadamuro, Ran Gilad-Bachrach, Jerry Zhu.

Optimal Defense Actions Against Test-Set Attacks.
Scott Alfeld, Paul Barford, Jerry Zhu.

Prediction Robustness: Accurate Prediction with Corrupted Features.
Lucas Janson, Lester Mackey.
10:00 Coffee Break
 10:30   Session 2: Risk-Sensitive Reinforcement Learning 
10:30

Invited Talk: Reliable RL through Risk Averseness.
Shie Mannor
 11:00   Contributed Talk: Learning Control Policies for Partially Observable Safety-Critical Systems.
 Gregory Kahn, Sergey Levine, Pieter Abbeel
 11:15   Invited Talk: Adversarial Training for Robust Learning.
 Paul Christiano
11:45

11:45-11:48


11:48-11:51


11:51-11:54


11:54-11:57


11:57-12:00

Poster spotlights 2

The 'Off-Switch'.
Dylan Hadfield-Menell, Anca Dragan, Pieter Abbeel, Stuart Russell.

Evaluation of Contextual Multi-armed Bandit for Automatic Operation Management.
Takuyaki Akiyama, Phong Nguyen, Hiroki Ohashi.

Optimally Robust Policy Improvement with Baseline Guarantees.
Yinlam Chow, Marek Petrik, Mohammad Ghavamzadeh.

A Novel Criterion for Adaptive Model Selection.
Jie Ding, Vahid Tarokh.

Situational Awareness by Risk-Conscious Skills.
Daniel J. Mankowitz, Aviv Tamar, Shie Mannor.
12:00 Lunch
 13:30   Session 3: Machine Learning and Security
13:30

Invited Talk: Machine Teaching and Security.
Jerry Zhu
14:00

Contributed Talk: Trusted Machine Learning for Probabilistic Models.
Shalini Ghosh, Patrick Lincoln, Ashish Tiwari, Jerry Zhu
14:15

Invited Talk: Security and Machine Learning: Lessons Learned and Future Challenges.
Dawn Song
14:45 Poster session / break
15:30 Session 4: Domain Adaptation and Causal Inference
15:30

Invited Talk: Counterfactual Inference for Market Design.
Susan Athey
16:00

Invited Talk: Robust Estimation of Parameter Accuracy in Domain Adaption.
Dean Foster
 16:30   Discussion
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