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cs.LG2024
An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks
Zhifa Ke, Zaiwen Wen, Junyu Zhang
Temporal difference (TD) learning algorithms with neural network function parameterization have well-established empirical success in many practical large-scale reinforcement learn…
math.OC2024
Oracle complexities of augmented Lagrangian methods for nonsmooth manifold optimization
Kangkang Deng, Jiang Hu, Jiayuan Wu +1
In this paper, we present two novel manifold inexact augmented Lagrangian methods, \textbf{ManIAL} for deterministic settings and \textbf{StoManIAL} for stochastic settings, solvin…