Wei Liu, Qihang Lin, Yangyang Xu, A near-optimal method for linearly constrained composite non-convex non-smooth problems. ARXIV

Wei Liu, Yangyang Xu, A single-loop SPIDER-type stochastic subgradient method for expectation-constrained nonconvex nonsmooth optimization. ARXIV

Wei Liu, Muhammad Khan, Gabriel Mancino-Ball, Yangyang Xu, A stochastic smoothing framework for nonconvex-nonconcave min-sum-max problems with applications to Wasserstein distributionally robust optimization.  ARXIV

Wei Liu, Qihang Lin, Yangyang Xu,  Lower complexity bound of first-order methods for affinely constrained composite non-convex non-smooth problems. ARXIV 

Wei Liu, Xin Liu, Michael K. Ng, Zaikun Zhang, A  graph-partitioning based continuous optimization approach to semi-supervised clustering problems. ARXIV

Hari Dahal, Wei Liu, Yangyang Xu, Damped proximal augmented Lagrangian method for weakly-convex problems with convex constraints. ARXIV

Wei Liu, Qihang Lin, Yangyang Xu, First-order methods for affinely constrained composite non-convex non-smooth problems: Lower complexity bound and near-optimal methods. ARXIV

Wei Liu, Xin Liu, and Xiaojun Chen, An inexact augmented Lagrangian algorithm for training leaky ReLU neural network with group sparsity. Journal of Machine Learning Research. 2023. ARXIV Code JMLR

Wei Liu, Xin Liu, and Xiaojun Chen, Linearly-constrained nonsmooth optimization for training autoencoders. SIAM Journal on Optimization. 2022. ARXIV Code SIOPT

Wei Liu, et al., Local training-based decentralized framework with adaptive gradient updates and compressed communication.

Wei Liu, Anweshit Panda, Ujwal Pandey, Christopher Brissette, Yikang Shen, George M. Slota, Naigang Wang, Jie Chen, Yangyang Xu, Compressed Decentralized Momentum Stochastic Gradient Methods for Nonconvex Optimization.  Accepted by Transactions on Machine Learning Research. ARXIV