5 papers · 1 filter
Bridging the Resource Gap: Deploying Advanced Imitation Learning Models onto Affordable Embedded Platforms
Haizhou Ge, Ruixiang Wang, Zhu-ang Xu +7
Advanced imitation learning with structures like the transformer is increasingly demonstrating its advantages in robotics. However, deploying these large-scale models on embedded p…
General Procedure to Provide High-Probability Guarantees for Stochastic Saddle Point Problems
Dongyang Li, Haobin Li, Junyu Zhang
This paper considers smooth strongly convex and strongly concave (SC-SC) stochastic saddle point (SSP) problems. Suppose there is an arbitrary oracle that in expectation returns an…
A Payoff-Based Policy Gradient Method in Stochastic Games with Long-Run Average Payoffs
Junyue Zhang, Yifen Mu
Despite the significant potential for various applications, stochastic games with long-run average payoffs have received limited scholarly attention, particularly concerning the de…
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…
Stochastic Bregman Proximal Gradient Method Revisited: Kernel Conditioning and Painless Variance Reduction
Junyu Zhang
We investigate stochastic Bregman proximal gradient (SBPG) methods for minimizing a finite-sum nonconvex function , where is convex an…