23 citations · 38 across the 8 of their papers we have counts for
4 papers · 2 filters
Markov Chain Block Coordinate Descent
Tao Sun, Yuejiao Sun, Yangyang Xu +1
The method of block coordinate gradient descent (BCD) has been a powerful method for large-scale optimization. This paper considers the BCD method that successively updates a serie…
Non-ergodic Convergence Analysis of Heavy-Ball Algorithms
Tao Sun, Penghang Yin, Dongsheng Li +3
In this paper, we revisit the convergence of the Heavy-ball method, and present improved convergence complexity results in the convex setting. We provide the first non-ergodic O(1/…
On Markov Chain Gradient Descent
Tao Sun, Yuejiao Sun, Wotao Yin
Stochastic gradient methods are the workhorse (algorithms) of large-scale optimization problems in machine learning, signal processing, and other computational sciences and enginee…
Non-ergodic Complexity of Convex Proximal Inertial Gradient Descents
Tao Sun, Linbo Qiao, Dongsheng Li
The proximal inertial gradient descent is efficient for the composite minimization and applicable for broad of machine learning problems. In this paper, we revisit the computationa…