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Sample Complexity Reduction via Policy Difference Estimation in Tabular Reinforcement Learning
by
Narang, Adhyyan
,
Wagenmaker, Andrew
,
Ratliff, Lillian
,
Jamieson, Kevin
Published in
arXiv.org
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On Targeted Manipulation and Deception when Optimizing LLMs for User Feedback
by
Williams, Marcus
,
Carroll, Micah
,
Narang, Adhyyan
,
Weisser, Constantin
,
Murphy, Brendan
,
Dragan, Anca
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arXiv.org
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Online SuBmodular + SuPermodular (BP) Maximization with Bandit Feedback
by
Narang, Adhyyan
,
Sadeghi, Omid
,
Ratliff, Lillian J
,
Fazel, Maryam
,
Bilmes, Jeff
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arXiv.org
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Multiplayer Performative Prediction: Learning in Decision-Dependent Games
by
Narang, Adhyyan
,
Faulkner, Evan
,
Drusvyatskiy, Dmitriy
,
Fazel, Maryam
,
Ratliff, Lillian J
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arXiv.org
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Towards Sample-efficient Overparameterized Meta-learning
by
Sun, Yue
,
Narang, Adhyyan
,
Halil Ibrahim Gulluk
,
Samet Oymak
,
Fazel, Maryam
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arXiv.org
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Classification vs regression in overparameterized regimes: Does the loss function matter?
by
Muthukumar, Vidya
,
Narang, Adhyyan
,
Subramanian, Vignesh
,
Belkin, Mikhail
,
Hsu, Daniel
,
Sahai, Anant
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arXiv.org
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Algorithms
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Machine Learning
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Combinatorial Analysis
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End User Training
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End Users
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Equilibrium
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Game Theory
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Interpolation
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Microbalances
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