Hybrid Variance-Reduced SGD Algorithms For Minimax Problems with Nonconvex-Linear Function. - Quoc Tran-Dinh; Deyi Liu; Lam M. Nguyen (NeurIPS, 2020)

Robust and Generalizable Visual Representation Learning via Random Convolutions. - Zhenlin Xu; Deyi Liu; Junlin Yang; Marc Niethammer (CoRR, 2020)

An Inexact Interior-Point Lagrangian Decomposition Algorithm with Inexact Oracles. - Deyi Liu; Quoc Tran-Dinh (J. Optim. Theory Appl., 2020)

Monitoring Method for Archival Data Change of Electrical Information Acquisition System Based On Data Middle Office and Its Application. - Weiqing Yao; Qiang Rao; Jiajun Yuan; Deyi Liu; Jie Xu (AIAM (ACM), 2021)

Robust and Generalizable Visual Representation Learning via Random Convolutions. - Zhenlin Xu; Deyi Liu; Junlin Yang; Colin Raffel; Marc Niethammer (ICLR, 2021)

An application of an automation operation and maintenance tool design and application. - Zhan Wu; Jundong Huang; Haohua Meng; Gang Li; Deyi Liu; Size Xiao (RICAI, 2022)

A Newton Frank-Wolfe method for constrained self-concordant minimization. - Deyi Liu; Volkan Cevher; Quoc Tran-Dinh (J. Glob. Optim., 2022)

New Primal-Dual Algorithms for a Class of Nonsmooth and Nonlinear Convex-Concave Minimax Problems. - Yuzixuan Zhu; Deyi Liu; Quoc Tran-Dinh (SIAM J. Optim., 2022)

Efficient and Provable Algorithms for Convex Optimization Problems Beyond Lipschitz Continuous Gradients. - Deyi Liu (2022)

A new randomized primal-dual algorithm for convex optimization with fast last iterate convergence rates. - Quoc Tran-Dinh; Deyi Liu (Optim. Methods Softw., 2023)

Model Merging in Pre-training of Large Language Models. - Yunshui Li; Yiyuan Ma; Shen Yan; Chaoyi Zhang; Jing Liu; Jianqiao Lu; Ziwen Xu; Mengzhao Chen; Minrui Wang; Shiyi Zhan; Jin Ma; Xunhao Lai; et al. (CoRR, 2025)