1 citations · 1 across the 4 of their papers we have counts for
4 papers
Convergence of Two Time-Scale Stochastic Approximation: A Martingale Approach
Mathukumalli Vidyasagar
In this paper, we analyze the two time-scale stochastic approximation (TTSSA) algorithm introduced in Borkar (1997) using a martingale approach. This approach leads to simple suffi…
Revisiting Stochastic Approximation and Stochastic Gradient Descent
Rajeeva Laxman Karandikar, Bhamidi Visweswara Rao, Mathukumalli Vidyasagar
In this paper, we introduce a new approach to proving the convergence of the Stochastic Approximation (SA) and the Stochastic Gradient Descent (SGD) algorithms. The new approach is…
Convergence Rates for Stochastic Approximation: Biased Noise with Unbounded Variance, and Applications
Rajeeva L. Karandikar, M. Vidyasagar
In this paper, we study the convergence properties of the Stochastic Gradient Descent (SGD) method for finding a stationary point of a given objective function . The obje…
Convergence of Batch Asynchronous Stochastic Approximation With Applications to Reinforcement Learning
Rajeeva L. Karandikar, M. Vidyasagar
We begin by briefly surveying some results on the convergence of the Stochastic Gradient Descent (SGD) Method, proved in a companion paper by the present authors. These results are…