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math.OC2022
How a Small Amount of Data Sharing Benefits Distributed Optimization and Learning : The Upside of Data Heterogeneity
Mingxi Zhu, Yinyu Ye
Distributed optimization algorithms are widely used in machine learning. This paper investigates how a small amount of data sharing can improve their performance. Focusing on gener…
math.OC2019★ 1 cited
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…
math.OC2019
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…