163 citations · 1.2k across the 128 of their papers we have counts for
5 papers · 2 filters
Adaptive Accelerated Gradient Converging Methods under Holderian Error Bound Condition
Mingrui Liu, Tianbao Yang
Recent studies have shown that proximal gradient (PG) method and accelerated gradient method (APG) with restarting can enjoy a linear convergence under a weaker condition than stro…
A Richer Theory of Convex Constrained Optimization with Reduced Projections and Improved Rates
Tianbao Yang, Qihang Lin, Lijun Zhang
This paper focuses on convex constrained optimization problems, where the solution is subject to a convex inequality constraint. In particular, we aim at challenging problems for w…
Homotopy Smoothing for Non-Smooth Problems with Lower Complexity than
Yi Xu, Yan Yan, Qihang Lin +1
In this paper, we develop a novel {\bf ho}moto{\bf p}y {\bf s}moothing (HOPS) algorithm for solving a family of non-smooth problems that is composed of a non-smooth term with an ex…
Accelerate Stochastic Subgradient Method by Leveraging Local Growth Condition
Yi Xu, Qihang Lin, Tianbao Yang
In this paper, a new theory is developed for first-order stochastic convex optimization, showing that the global convergence rate is sufficiently quantified by a local growth rate…
Unified Convergence Analysis of Stochastic Momentum Methods for Convex and Non-convex Optimization
Tianbao Yang, Qihang Lin, Zhe Li
Recently, {\it stochastic momentum} methods have been widely adopted in training deep neural networks. However, their convergence analysis is still underexplored at the moment, in…