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Poster
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Tue 14:00
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Reinforcement Learning with Logarithmic Regret and Policy Switches
Grigoris Velegkas · Zhuoran Yang · Amin Karbasi
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Poster
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Trustworthy Monte Carlo
Juha Harviainen · Mikko Koivisto · Petteri Kaski
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Poster
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Thu 9:00
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Statistically Meaningful Approximation: a Case Study on Approximating Turing Machines with Transformers
Colin Wei · Yining Chen · Tengyu Ma
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Poster
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On the role of overparameterization in off-policy Temporal Difference learning with linear function approximation
Valentin Thomas
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Poster
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Tue 9:00
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A Multilabel Classification Framework for Approximate Nearest Neighbor Search
Ville Hyvönen · Elias Jääsaari · Teemu Roos
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Poster
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Tue 14:00
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Theory and Approximate Solvers for Branched Optimal Transport with Multiple Sources
Peter Lippmann · Enrique Fita Sanmartín · Fred Hamprecht
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Poster
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Thu 14:00
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Generic bounds on the approximation error for physics-informed (and) operator learning
Tim De Ryck · Siddhartha Mishra
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Poster
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Tue 9:00
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Instance-Dependent Near-Optimal Policy Identification in Linear MDPs via Online Experiment Design
Andrew Wagenmaker · Kevin Jamieson
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Poster
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Thu 14:00
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Fair Rank Aggregation
Diptarka Chakraborty · Syamantak Das · Arindam Khan · Aditya Subramanian
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Poster
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Thu 14:00
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Provably Efficient Model-Free Constrained RL with Linear Function Approximation
Arnob Ghosh · Xingyu Zhou · Ness Shroff
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Poster
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Tue 9:00
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A general approximation lower bound in Lp norm, with applications to feed-forward neural networks
El Mehdi Achour · Armand Foucault · Sébastien Gerchinovitz · François Malgouyres
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Workshop
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Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint
Hao Liu · Minshuo Chen · Siawpeng Er · Wenjing Liao · Tong Zhang · Tuo Zhao
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