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Dawen Liang

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Switching the Loss Reduces the Cost in Batch Reinforcement Learning

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Mar 12, 2024
Alex Ayoub, Kaiwen Wang, Vincent Liu, Samuel Robertson, James McInerney, Dawen Liang, Nathan Kallus, Csaba Szepesvári

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Risk-Sensitive RL with Optimized Certainty Equivalents via Reduction to Standard RL

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Mar 10, 2024
Kaiwen Wang, Dawen Liang, Nathan Kallus, Wen Sun

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Off-Policy Evaluation for Large Action Spaces via Policy Convolution

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Oct 24, 2023
Noveen Sachdeva, Lequn Wang, Dawen Liang, Nathan Kallus, Julian McAuley

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Large Language Models as Zero-Shot Conversational Recommenders

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Aug 19, 2023
Zhankui He, Zhouhang Xie, Rahul Jha, Harald Steck, Dawen Liang, Yesu Feng, Bodhisattwa Prasad Majumder, Nathan Kallus, Julian McAuley

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Local Policy Improvement for Recommender Systems

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Dec 22, 2022
Dawen Liang, Nikos Vlassis

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Learning Correlated Latent Representations with Adaptive Priors

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Jul 16, 2019
Da Tang, Dawen Liang, Nicholas Ruozzi, Tony Jebara

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Correlated Variational Auto-Encoders

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May 16, 2019
Da Tang, Dawen Liang, Tony Jebara, Nicholas Ruozzi

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The Deconfounded Recommender: A Causal Inference Approach to Recommendation

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Aug 20, 2018
Yixin Wang, Dawen Liang, Laurent Charlin, David M. Blei

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Variational Autoencoders for Collaborative Filtering

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Feb 16, 2018
Dawen Liang, Rahul G. Krishnan, Matthew D. Hoffman, Tony Jebara

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On the challenges of learning with inference networks on sparse, high-dimensional data

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Oct 17, 2017
Rahul G. Krishnan, Dawen Liang, Matthew Hoffman

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