34 citations · 89 across the 29 of their papers we have counts for
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math.OC2019
Regularized Diffusion Adaptation via Conjugate Smoothing
Stefan Vlaski, Lieven Vandenberghe, Ali H. Sayed
The purpose of this work is to develop and study a distributed strategy for Pareto optimization of an aggregate cost consisting of regularized risks. Each risk is modeled as the ex…
math.OC2019
Second-Order Guarantees of Stochastic Gradient Descent in Non-Convex Optimization
Stefan Vlaski, Ali H. Sayed
Recent years have seen increased interest in performance guarantees of gradient descent algorithms for non-convex optimization. A number of works have uncovered that gradient noise…
math.OC2019
Distributed Learning in Non-Convex Environments -- Part I: Agreement at a Linear Rate
Stefan Vlaski, Ali H. Sayed
Driven by the need to solve increasingly complex optimization problems in signal processing and machine learning, there has been increasing interest in understanding the behavior o…