15 citations · 20 across the 11 of their papers we have counts for
5 papers · 1 filter
Finite-Time Analysis of Stochastic Nonconvex Nonsmooth Optimization on the Riemannian Manifolds
Emre Sahinoglu, Youbang Sun, Shahin Shahrampour
This work addresses the finite-time analysis of nonsmooth nonconvex stochastic optimization under Riemannian manifold constraints. We adapt the notion of Goldstein stationarity to…
Local Linear Convergence of Infeasible Optimization with Orthogonal Constraints
Youbang Sun, Shixiang Chen, Alfredo Garcia +1
Many classical and modern machine learning algorithms require solving optimization tasks under orthogonality constraints. Solving these tasks with feasible methods requires a gradi…
On Centralized and Distributed Mirror Descent: Convergence Analysis Using Quadratic Constraints
Youbang Sun, Mahyar Fazlyab, Shahin Shahrampour
Mirror descent (MD) is a powerful first-order optimization technique that subsumes several optimization algorithms including gradient descent (GD). In this work, we develop a semi-…
Linear Convergence of Distributed Mirror Descent with Integral Feedback for Strongly Convex Problems
Youbang Sun, Shahin Shahrampour
Distributed optimization often requires finding the minimum of a global objective function written as a sum of local functions. A group of agents work collectively to minimize the…
Distributed Mirror Descent with Integral Feedback: Asymptotic Convergence Analysis of Continuous-time Dynamics
Youbang Sun, Shahin Shahrampour
This work addresses distributed optimization, where a network of agents wants to minimize a global strongly convex objective function. The global function can be written as a sum o…