10 citations · 21 across the 9 of their papers we have counts for
10 papers · 1 filter
SOLNP+: A Derivative-Free Solver for Constrained Nonlinear Optimization
Dongdong Ge, Tianhao Liu, Jinsong Liu +2
SOLNP+ is a derivative-free solver for constrained nonlinear optimization. It starts from SOLNP proposed in 1989 by Ye Ye with the main idea that uses finite difference to approxim…
Distributed stochastic optimization with large delays
Zhengyuan Zhou, Panayotis Mertikopoulos, Nicholas Bambos +2
One of the most widely used methods for solving large-scale stochastic optimization problems is distributed asynchronous stochastic gradient descent (DASGD), a family of algorithms…
On a Randomized Multi-Block ADMM for Solving Selected Machine Learning Problems
Mingxi Zhu, Kresimir Mihic, Yinyu Ye
The Alternating Direction Method of Multipliers (ADMM) has now days gained tremendous attentions for solving large-scale machine learning and signal processing problems due to the…
Interior-Point Methods Strike Back: Solving the Wasserstein Barycenter Problem
Dongdong Ge, Haoyue Wang, Zikai Xiong +1
Computing the Wasserstein barycenter of a set of probability measures under the optimal transport metric can quickly become prohibitive for traditional second-order algorithms, suc…
Managing Randomization in the Multi-Block Alternating Direction Method of Multipliers for Quadratic Optimization
Kresimir Mihic, Mingxi Zhu, Yinyu Ye
The Alternating Direction Method of Multipliers (ADMM) has gained a lot of attention for solving large-scale and objective-separable constrained optimization. However, the two-bloc…
Near-Optimal Time and Sample Complexities for Solving Discounted Markov Decision Process with a Generative Model
Aaron Sidford, Mengdi Wang, Xian Wu +2
In this paper we consider the problem of computing an -optimal policy of a discounted Markov Decision Process (DMDP) provided we can only access its transition function through…