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Using Machine Teaching to Investigate Human Assumptions when Teaching Reinforcement Learners

Sep 05, 2020
Yun-Shiuan Chuang, Xuezhou Zhang, Yuzhe Ma, Mark K. Ho, Joseph L. Austerweil, Xiaojin Zhu

* 21 pages, 4 figures 

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Task-agnostic Exploration in Reinforcement Learning

Jun 16, 2020
Xuezhou Zhang, Yuzhe ma, Adish Singla


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The Teaching Dimension of Q-learning

Jun 16, 2020
Xuezhou Zhang, Shubham Kumar Bharti, Yuzhe Ma, Adish Singla, Xiaojin Zhu


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Neural Additive Models: Interpretable Machine Learning with Neural Nets

Apr 29, 2020
Rishabh Agarwal, Nicholas Frosst, Xuezhou Zhang, Rich Caruana, Geoffrey E. Hinton


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Adaptive Reward-Poisoning Attacks against Reinforcement Learning

Mar 27, 2020
Xuezhou Zhang, Yuzhe Ma, Adish Singla, Xiaojin Zhu


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Policy Poisoning in Batch Reinforcement Learning and Control

Oct 31, 2019
Yuzhe Ma, Xuezhou Zhang, Wen Sun, Xiaojin Zhu

* NeurIPS 2019 

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Online Data Poisoning Attack

Mar 05, 2019
Xuezhou Zhang, Xiaojin Zhu


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Interpretability is Harder in the Multiclass Setting: Axiomatic Interpretability for Multiclass Additive Models

Oct 22, 2018
Xuezhou Zhang, Sarah Tan, Paul Koch, Yin Lou, Urszula Chajewska, Rich Caruana

* Preprint 

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An Optimal Control Approach to Sequential Machine Teaching

Oct 16, 2018
Laurent Lessard, Xuezhou Zhang, Xiaojin Zhu


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Teacher Improves Learning by Selecting a Training Subset

Feb 25, 2018
Yuzhe Ma, Robert Nowak, Philippe Rigollet, Xuezhou Zhang, Xiaojin Zhu

* AISTATS 2018 

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Training Set Debugging Using Trusted Items

Jan 24, 2018
Xuezhou Zhang, Xiaojin Zhu, Stephen J. Wright

* AAAI 2018 

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