Guannan Liang

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 20

Top Topics

Sparse Learning

Matrix Completion

Differentially Private

Top Venues

Publications

Guannan Liang, Qianqian Tong, Jiahao Ding, Miao Pan, Jinbo Bi
Stochastic privacy-preserving methods for nonconvex sparse learning. Inf. Sci. 630 (2023)
Qianqian Tong, Guannan Liang, Jiahao Ding, Tan Zhu, Miao Pan, Jinbo Bi
Federated Optimization of ℓ0-norm Regularized Sparse Learning. Algorithms 15 (9) (2022)
Qianqian Tong, Guannan Liang, Jinbo Bi
Calibrating the adaptive learning rate to improve convergence of ADAM. Neurocomputing 481 (2022)
Yang Shi, Guannan Liang, Young-joo Chung
Meta-Shop: Improving Item Advertisement For Small Businesses. CoRR (2022)
Qianqian Tong, Guannan Liang, Xingyu Cai, Chunjiang Zhu, Jinbo Bi
Asynchronous parallel stochastic Quasi-Newton methods. Parallel Comput. 101 (2021)
Ramin Raziperchikolaei, Guannan Liang, Young-joo Chung
Shared Neural Item Representations for Completely Cold Start Problem. RecSys (2021)
Tan Zhu, Guannan Liang, Chunjiang Zhu, Haining Li, Jinbo Bi
An Efficient Algorithm for Deep Stochastic Contextual Bandits. AAAI (2021)
Guannan Liang, Qianqian Tong, Chunjiang Zhu, Jinbo Bi
Escaping Saddle Points with Stochastically Controlled Stochastic Gradient Methods. CoRR (2021)
Tan Zhu, Guannan Liang, Chunjiang Zhu, Haining Li, Jinbo Bi
An Efficient Algorithm for Deep Stochastic Contextual Bandits. CoRR (2021)
Jiahao Ding, Guannan Liang, Jinbo Bi, Miao Pan
Differentially Private and Communication Efficient Collaborative Learning. AAAI (2021)
Qianqian Tong, Guannan Liang, Tan Zhu, Jinbo Bi
Federated Nonconvex Sparse Learning. CoRR (2021)
Guannan Liang, Qianqian Tong, Jiahao Ding, Miao Pan, Jinbo Bi
Effective Proximal Methods for Non-convex Non-smooth Regularized Learning. ICDM (2020)
Guannan Liang, Qianqian Tong, Chun Jiang Zhu, Jinbo Bi
An Effective Hard Thresholding Method Based on Stochastic Variance Reduction for Nonconvex Sparse Learning. AAAI (2020)
Jiahao Ding, Jingyi Wang, Guannan Liang, Jinbo Bi, Miao Pan
Towards Plausible Differentially Private ADMM Based Distributed Machine Learning. CoRR (2020)
Qianqian Tong, Guannan Liang, Jinbo Bi
Effective Federated Adaptive Gradient Methods with Non-IID Decentralized Data. CoRR (2020)
Qianqian Tong, Guannan Liang, Xingyu Cai, Chun Jiang Zhu, Jinbo Bi
Asynchronous Parallel Stochastic Quasi-Newton Methods. CoRR (2020)
Guannan Liang, Qianqian Tong, Jiahao Ding, Miao Pan, Jinbo Bi
Effective Proximal Methods for Non-convex Non-smooth Regularized Learning. CoRR (2020)
Jiahao Ding, Jingyi Wang, Guannan Liang, Jinbo Bi, Miao Pan
Towards Plausible Differentially Private ADMM Based Distributed Machine Learning. CIKM (2020)
Qianqian Tong, Guannan Liang, Jinbo Bi
Calibrating the Learning Rate for Adaptive Gradient Methods to Improve Generalization Performance. CoRR (2019)
Jin Lu, Guannan Liang, Jiangwen Sun, Jinbo Bi
A Sparse Interactive Model for Matrix Completion with Side Information. NIPS (2016)