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Poster
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Wed 16:30
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A Nearly Optimal and Low-Switching Algorithm for Reinforcement Learning with General Function Approximation
Heyang Zhao · Jiafan He · Quanquan Gu
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Poster
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Fri 16:30
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Pretrained Transformer Efficiently Learns Low-Dimensional Target Functions In-Context
Kazusato Oko · Yujin Song · Taiji Suzuki · Denny Wu
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Poster
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Wed 16:30
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Realizable H-Consistent and Bayes-Consistent Loss Functions for Learning to Defer
Anqi Mao · Mehryar Mohri · Yutao Zhong
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Poster
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Wed 11:00
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Kernel-Based Function Approximation for Average Reward Reinforcement Learning: An Optimist No-Regret Algorithm
Sattar Vakili · Julia Olkhovskaya
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Workshop
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Invariant Graphon Networks: Approximation and Cut Distance
Daniel Herbst · Stefanie Jegelka
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Poster
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Wed 11:00
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Statistical-Computational Trade-offs for Density Estimation
Anders Aamand · Alexandr Andoni · Justin Chen · Piotr Indyk · Shyam Narayanan · Sandeep Silwal · Haike Xu
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Poster
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Fri 16:30
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Randomized Exploration for Reinforcement Learning with Multinomial Logistic Function Approximation
Wooseong Cho · Taehyun Hwang · Joongkyu Lee · Min-hwan Oh
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Poster
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An Analytical Study of Utility Functions in Multi-Objective Reinforcement Learning
Manel Rodríguez Soto · Juan A Rodríguez-Aguilar · Maite López-Sánchez
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Workshop
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What should a neuron aim for? Designing local objective functions based on information theory
Andreas Schneider · Valentin Neuhaus · David A. Ehrlich · Alexander Ecker · Abdullah Makkeh · Viola Priesemann · Michael Wibral
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