2 citations · 3 across the 3 of their papers we have counts for
3 papers
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…
cs.DC2021★ 2 cited
Highway: Efficient Consensus with Flexible Finality
Daniel Kane, Andreas Fackler, Adam Gągol +1
There has been recently a lot of progress in designing efficient partially synchronous BFT consensus protocols that are meant to serve as core consensus engines for Proof of Stake…