15 citations · 20 across the 11 of their papers we have counts for
11 papers
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…
ADARL: Adaptive Low-Rank Structures for Robust Policy Learning under Uncertainty
Chenliang Li, Junyu Leng, Jiaxiang Li +4
Robust reinforcement learning (Robust RL) seeks to handle epistemic uncertainty in environment dynamics, but existing approaches often rely on nested min--max optimization, which i…
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…
Linear Convergence of Independent Natural Policy Gradient in Games with Entropy Regularization
Youbang Sun, Tao Liu, P. R. Kumar +1
This work focuses on the entropy-regularized independent natural policy gradient (NPG) algorithm in multi-agent reinforcement learning. In this work, agents are assumed to have acc…
Retraction-Free Decentralized Non-convex Optimization with Orthogonal Constraints
Youbang Sun, Shixiang Chen, Alfredo Garcia +1
In this paper, we investigate decentralized non-convex optimization with orthogonal constraints. Conventional algorithms for this setting require either manifold retractions or oth…
Provably Fast Convergence of Independent Natural Policy Gradient for Markov Potential Games
Youbang Sun, Tao Liu, Ruida Zhou +2
This work studies an independent natural policy gradient (NPG) algorithm for the multi-agent reinforcement learning problem in Markov potential games. It is shown that, under mild…
On the Stability Analysis of Open Federated Learning Systems
Youbang Sun, Heshan Fernando, Tianyi Chen +1
We consider the open federated learning (FL) systems, where clients may join and/or leave the system during the FL process. Given the variability of the number of present clients,…
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…
Can I trust you more? Model-Agnostic Hierarchical Explanations
Michael Tsang, Youbang Sun, Dongxu Ren +1
Interactions such as double negation in sentences and scene interactions in images are common forms of complex dependencies captured by state-of-the-art machine learning models. We…