A Sparse Interactive Model for Matrix Completion with Side Information. - Jin Lu 001; Guannan Liang; Jiangwen Sun; Jinbo Bi (NIPS, 2016)

Calibrating the Learning Rate for Adaptive Gradient Methods to Improve Generalization Performance. - Qianqian Tong; Guannan Liang; Jinbo Bi (CoRR, 2019)

An Effective Hard Thresholding Method Based on Stochastic Variance Reduction for Nonconvex Sparse Learning. - Guannan Liang; Qianqian Tong; Chunjiang Zhu; Jinbo Bi (AAAI, 2020)

Towards Plausible Differentially Private ADMM Based Distributed Machine Learning. - Jiahao Ding; Jingyi Wang 002; Guannan Liang; Jinbo Bi; Miao Pan (CIKM, 2020)

Effective Proximal Methods for Non-convex Non-smooth Regularized Learning. - Guannan Liang; Qianqian Tong; Jiahao Ding; Miao Pan; Jinbo Bi (ICDM, 2020)

Effective Federated Adaptive Gradient Methods with Non-IID Decentralized Data. - Qianqian Tong; Guannan Liang; Jinbo Bi (CoRR, 2020)

Differentially Private and Communication Efficient Collaborative Learning. - Jiahao Ding; Guannan Liang; Jinbo Bi; Miao Pan (AAAI, 2021)

An Efficient Algorithm for Deep Stochastic Contextual Bandits. - Tan Zhu; Guannan Liang; Chunjiang Zhu; Haining Li; Jinbo Bi (AAAI, 2021)

Shared Neural Item Representations for Completely Cold Start Problem. - Ramin Raziperchikolaei; Guannan Liang; Young-joo Chung (RecSys, 2021)

Federated Nonconvex Sparse Learning. - Qianqian Tong; Guannan Liang; Tan Zhu; Jinbo Bi (CoRR, 2021)

Escaping Saddle Points with Stochastically Controlled Stochastic Gradient Methods. - Guannan Liang; Qianqian Tong; Chunjiang Zhu; Jinbo Bi (CoRR, 2021)

Asynchronous parallel stochastic Quasi-Newton methods. - Qianqian Tong; Guannan Liang; Xingyu Cai; Chunjiang Zhu; Jinbo Bi (Parallel Comput., 2021)

Federated Optimization of ℓ0-norm Regularized Sparse Learning. - Qianqian Tong; Guannan Liang; Jiahao Ding; Tan Zhu; Miao Pan; Jinbo Bi (Algorithms, 2022)

Meta-Shop: Improving Item Advertisement For Small Businesses. - Yang Shi; Guannan Liang; Young-joo Chung (CoRR, 2022)

Calibrating the adaptive learning rate to improve convergence of ADAM. - Qianqian Tong; Guannan Liang; Jinbo Bi (Neurocomputing, 2022)

Stochastic privacy-preserving methods for nonconvex sparse learning. - Guannan Liang; Qianqian Tong; Jiahao Ding; Miao Pan; Jinbo Bi (Inf. Sci., 2023)

LLM-Powered AI Agent Systems and Their Applications in Industry. - Guannan Liang; Qianqian Tong (CoRR, 2025)