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stat.ML2024
The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize
Dongyan Huo, Yixuan Zhang, Yudong Chen +1
In this work, we investigate stochastic approximation (SA) with Markovian data and nonlinear updates under constant stepsize . Existing work has primarily focused on either i.…
stat.ML2024
Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive SA
Yixuan Zhang, Dongyan Huo, Yudong Chen +1
Motivated by Q-learning, we study nonsmooth contractive stochastic approximation (SA) with constant stepsize. We focus on two important classes of dynamics: 1) nonsmooth contractiv…
stat.ML2024★ 1 cited
Constant Stepsize Q-learning: Distributional Convergence, Bias and Extrapolation
Yixuan Zhang, Qiaomin Xie
Stochastic Approximation (SA) is a widely used algorithmic approach in various fields, including optimization and reinforcement learning (RL). Among RL algorithms, Q-learning is pa…