1 citations · 1 across the 3 of their papers we have counts for
3 papers
quant-ph2024
Improved classical shadows from local symmetries in the Schur basis
Daniel Grier, Sihan Liu, Gaurav Mahajan
We study the sample complexity of the classical shadows task: what is the fewest number of copies of an unknown state you need to measure to predict expected values with respect to…
cs.LG2023★ 1 cited
Exponential Hardness of Reinforcement Learning with Linear Function Approximation
Daniel Kane, Sihan Liu, Shachar Lovett +3
A fundamental question in reinforcement learning theory is: suppose the optimal value functions are linear in given features, can we learn them efficiently? This problem's counterp…
cs.GT2022
Sampling Equilibria: Fast No-Regret Learning in Structured Games
Daniel Beaglehole, Max Hopkins, Daniel Kane +2
Learning and equilibrium computation in games are fundamental problems across computer science and economics, with applications ranging from politics to machine learning. Much of t…