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Found 4 papers, 0 papers with code
The Collusion of Memory and Nonlinearity in Stochastic Approximation With Constant Stepsize
By leveraging the smoothness and recurrence properties of the SA updates, we develop a fine-grained analysis of the correlation between the SA iterates $\theta_k$ and Markovian data $x_k$.
Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive SA
Motivated by Q-learning, we study nonsmooth contractive stochastic approximation (SA) with constant stepsize.
Effectiveness of Constant Stepsize in Markovian LSA and Statistical Inference
Our procedure leverages the fast mixing property of constant-stepsize LSA for better covariance estimation and employs Richardson-Romberg (RR) extrapolation to reduce the bias induced by constant stepsize and Markovian data.
Bias and Extrapolation in Markovian Linear Stochastic Approximation with Constant Stepsizes
We consider Linear Stochastic Approximation (LSA) with a constant stepsize and Markovian data.
