12 Results

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