Stochastic linear optimization never overfits with quadratically-bounded losses on general data

14 February 2022

Papers citing "Stochastic linear optimization never overfits with quadratically-bounded losses on general data"

4 / 4 papers shown

Title
Rates of Convergence in the Central Limit Theorem for Markov Chains, with an Application to TD Learning R. Srikant 44 5 0 28 Jan 2024
Unconstrained Online Learning with Unbounded Losses Andrew Jacobsen Ashok Cutkosky 32 16 0 08 Jun 2023
Actor-critic is implicitly biased towards high entropy optimal policies Yuzheng Hu Ziwei Ji Matus Telgarsky 60 11 0 21 Oct 2021
A High Probability Analysis of Adaptive SGD with Momentum Xiaoyun Li Francesco Orabona 92 65 0 28 Jul 2020