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Tue 14:00 Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations.
Neil Jethani · Mukund Sudarshan · Yindalon Aphinyanaphongs · Rajesh Ranganath
Tue 14:00 Improving Classifier Confidence using Lossy Label-Invariant Transformations
Sooyong Jang · Insup Lee · James Weimer
Tue 14:00 Shapley Flow: A Graph-based Approach to Interpreting Model Predictions
Jiaxuan Wang · Jenna Wiens · Scott Lundberg
Tue 14:00 Influence Decompositions For Neural Network Attribution
Kyle Reing · Greg Ver Steeg · Aram Galstyan
Thu 7:30 Online Sparse Reinforcement Learning
Botao Hao · Tor Lattimore · Csaba Szepesvari · Mengdi Wang
Thu 7:30 On Information Gain and Regret Bounds in Gaussian Process Bandits
Sattar Vakili · Kia Khezeli · Victor Picheny
Tue 18:30 Causal Modeling with Stochastic Confounders
Thanh Vinh Vo · Pengfei Wei · Wicher Bergsma · Tze Yun Leong