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Communication Efficient Primal-Dual Algorithm for Nonconvex Nonsmooth Distributed Optimization
Decentralized optimization problems frequently appear in the large scale machine learning problems. However, few works work on the …
Congliang Chen, Jiawei Zhang, Li Shen, Peilin Zhao, Zhiquan Luo
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When Expressivity Meets Trainability: Fewer than $n$ Neurons Can Work
Modern neural networks are often quite wide, causing large memory and computation costs. It is thus of great interest to train a …
Jiawei Zhang, Yushun Zhang, Mingyi Hong, Ruoyu Sun, Zhi-Quan Luo
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A Proximal Dual Consensus Method for Linearly Coupled Multi-Agent Non-Convex Optimization
Motivated by large-scale signal processing and machine learning applications, this paper considers the distributed multi-agent …
Jiawei Zhang, Songyang Ge, Tsung-Hui Chang, Zhi-Quan Luo
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A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems
Nonconvex-concave min-max problem arises in many machine learning applications including minimizing a pointwise maximum of a set of …
Jiawei Zhang, Peijun Xiao, Ruoyu Sun, Zhiquan Luo
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Scalable Gaussian Process Using Inexact ADMM for Big Data
Gaussian process (GP) for machine learning has been well studied over the past two decades and is now widely used in many sectors. …
Yue Xu, Feng Yin, Jiawei Zhang, Wenjun Xu, Shuguang Cui, Zhi-Quan Luo
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Learning Word Vectors with Linear Constraints: A Matrix Factorization Approach
Learning vector space representation of words, or word embedding, has attracted much recent research attention. With the objective of …
Wenye Li, Jiawei Zhang, Jianjun Zhou, Laizhong Cui
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