Publications

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

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

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

Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Changxin Liu, Yong Zhang (2022). Improving Fairness for Data Valuation in Federated Learning. In IEEE International Conference on Data Engineerin (ICDE) 2022.

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

Zhenan Fan*, Huang Fang*, Michael P. Friedlander (2022). A dual approach for federated learning. (* equal contribution).

Huang Fang (2021). First-order methods for structured optimization. PhD Dissertation.

Zhenan Fan*, Huang Fang*, Michael P. Friedlander (2021). Safe-screening rules for atomic-norm regularization. (* equal contribution). Submitted.

Huang Fang, Guanhua Fang, Tan Yu, Ping Li (2021). Efficient Greedy Coordinate Descent via Variable Partitioning. In UAI 2021.

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

Huang Fang, Nicholas J. A. Harvey, Victor S. Portella, Michael P. Friedlander (2020). Online mirror descent and dual averaging: keeping pace in the dynamic case. In ICML 2020. Extended version appeared in JMLR 2022.

PDF Journal PDF

Huang Fang, Zhenan Fan, Yifan Sun, Michael P. Friedlander (2020). Greed meets sparsity: understanding and improving greedy coordinate descent for sparse optimization. In AISTATS 2020.

Huang Fang, Minhao Cheng, Cho-Jui Hsieh, Michael P. Friedlander (2019). Fast training for large-scale one-versus-all linear classifiers using tree-structured initialization. In SDM 2019.

PDF Code Supplements

Huang Fang, Minhao Cheng, Cho-Jui Hsieh (2017). A Hyperplane-based Algorithm for Semi-supervised Dimension Reduction. In ICDM 2017.

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