3D Spatial Analysis Oriented Hybrid P2P Computing. - Xicheng Tan; Huang Fang (CSO (2), 2009)

A Hyperplane-Based Algorithm for Semi-Supervised Dimension Reduction. - Huang Fang; Minhao Cheng; Cho-Jui Hsieh (ICDM, 2017)

Improved Bounded Matrix Completion for Large-Scale Recommender Systems. - Huang Fang; Zhen Zhang; Yiqun Shao; Cho-Jui Hsieh (IJCAI, 2017)

Fast Training for Large-Scale One-versus-All Linear Classifiers using Tree-Structured Initialization. - Huang Fang; Minhao Cheng; Cho-Jui Hsieh; Michael P. Friedlander (SDM, 2019)

Greed Meets Sparsity: Understanding and Improving Greedy Coordinate Descent for Sparse Optimization. - Huang Fang; Zhenan Fan; Yifan Sun 001; Michael P. Friedlander (AISTATS, 2020)

Fast convergence of stochastic subgradient method under interpolation. - Huang Fang; Zhenan Fan; Michael P. Friedlander (ICLR, 2021)

Efficient greedy coordinate descent via variable partitioning. - Huang Fang; Guanhua Fang; Tan Yu; Ping Li 001 (UAI, 2021)

Improving Fairness for Data Valuation in Federated Learning. - Zhenan Fan; Huang Fang; Zirui Zhou; Jian Pei 001; Michael P. Friedlander; Changxin Liu 001; Yong Zhang 004 (CoRR, 2021)

Improving Fairness for Data Valuation in Horizontal Federated Learning. - Zhenan Fan; Huang Fang; Zirui Zhou; Jian Pei 001; Michael P. Friedlander; Changxin Liu 001; Yong Zhang 004 (ICDE, 2022)

Fair and efficient contribution valuation for vertical federated learning. - Zhenan Fan; Huang Fang; Zirui Zhou; Jian Pei 001; Michael P. Friedlander; Yong Zhang 004 (CoRR, 2022)

A dual approach for federated learning. - Zhenan Fan; Huang Fang; Michael P. Friedlander (CoRR, 2022)

Online Mirror Descent and Dual Averaging: Keeping Pace in the Dynamic Case. - Huang Fang; Nicholas J. A. Harvey; Victor S. Portella; Michael P. Friedlander (J. Mach. Learn. Res., 2022)

Global mantle clinopyroxene data (major and trace elements). - Ben Qin; Huang Fang; Huang Shichun; Andre Python; Yunfeng Chen; ZhangZhou J (GRO.data, 2022)

Global mantle clinopyroxene data (major and trace elements). - Ben Qin; Huang Fang; Huang Shichun; Andre Python; Yunfeng Chen; ZhangZhou J (GRO.data, 2022)

Improved Convergence of Differential Private SGD with Gradient Clipping. - Huang Fang; Xiaoyun Li; Chenglin Fan; Ping Li 001 (ICLR, 2023)

Differentiable Neuro-Symbolic Reasoning on Large-Scale Knowledge Graphs. - Shengyuan Chen; Yunfeng Cai; Huang Fang; Xiao Huang 001; Mingming Sun 001 (NeurIPS, 2023)

MLN4KB: an efficient Markov logic network engine for large-scale knowledge bases and structured logic rules. - Huang Fang; Yang Liu 320; Yunfeng Cai; Mingming Sun 001 (WWW, 2023)

MQuinE: a Cure for "Z-paradox" in Knowledge Graph Embedding. - Yang Liu 320; Huang Fang; Yunfeng Cai; Mingming Sun 001 (EMNLP, 2024)

Fair and Efficient Contribution Valuation for Vertical Federated Learning. - Zhenan Fan; Huang Fang; Xinglu Wang; Zirui Zhou; Jian Pei 001; Michael P. Friedlander; Yong Zhang 004 (ICLR, 2024)

Secure Causal Reasoning on Coarsened Graph for Privacy-aware Social Web Services. - Yang Liu 320; Chuan Zhou 001; Huang Fang; Peng Zhang 001; Yiling Pang; Qingzhao Zhang; Zhao Li 007; Hongyang Chen (ICWS, 2024)

MQuinE: a cure for "Z-paradox" in knowledge graph embedding models. - Yang Liu 320; Huang Fang; Yunfeng Cai; Mingming Sun 001 (CoRR, 2024)

MA-RLHF: Reinforcement Learning from Human Feedback with Macro Actions. - Yekun Chai; Haoran Sun; Huang Fang; Shuohuan Wang; Yu Sun 004; Hua Wu 003 (CoRR, 2024)

Cardinality-constrained structured data-fitting problems. - Zhenan Fan; Huang Fang; Michael P. Friedlander (Open J. Math. Optim., 2024)

MA-RLHF: Reinforcement Learning from Human Feedback with Macro Actions. - Yekun Chai; Haoran Sun; Huang Fang; Shuohuan Wang; Yu Sun; Hua Wu 003 (ICLR, 2025)