Huang Fang

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 19

Top Topics

Linear Classifiers

Simple And Easy To Implement

Sparsity Inducing

Top Venues

Open J. Math. Optim.

Publications

Zhenan Fan, Huang Fang, Michael P. Friedlander
Cardinality-constrained structured data-fitting problems. Open J. Math. Optim. 5 (2024)
Yang Liu, Huang Fang, Yunfeng Cai, Mingming Sun
MQuinE: a cure for "Z-paradox" in knowledge graph embedding models. CoRR (2024)
Zhenan Fan, Huang Fang, Xinglu Wang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Yong Zhang
Fair and Efficient Contribution Valuation for Vertical Federated Learning. ICLR (2024)
Shengyuan Chen, Yunfeng Cai, Huang Fang, Xiao Huang, Mingming Sun
Differentiable Neuro-Symbolic Reasoning on Large-Scale Knowledge Graphs. NeurIPS (2023)
Huang Fang, Yang Liu, Yunfeng Cai, Mingming Sun
MLN4KB: an efficient Markov logic network engine for large-scale knowledge bases and structured logic rules. WWW (2023)
Huang Fang, Xiaoyun Li, Chenglin Fan, Ping Li
Improved Convergence of Differential Private SGD with Gradient Clipping. ICLR (2023)
Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Yong Zhang
Fair and efficient contribution valuation for vertical federated learning. CoRR (2022)
Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Changxin Liu, Yong Zhang
Improving Fairness for Data Valuation in Horizontal Federated Learning. ICDE (2022)
Huang Fang, Nicholas J. A. Harvey, Victor S. Portella, Michael P. Friedlander
Online Mirror Descent and Dual Averaging: Keeping Pace in the Dynamic Case. J. Mach. Learn. Res. 23 (2022)
Zhenan Fan, Huang Fang, Michael P. Friedlander
A dual approach for federated learning. CoRR (2022)
Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Changxin Liu, Yong Zhang
Improving Fairness for Data Valuation in Federated Learning. CoRR (2021)
Huang Fang, Zhenan Fan, Michael P. Friedlander
Fast convergence of stochastic subgradient method under interpolation. ICLR (2021)
Huang Fang, Guanhua Fang, Tan Yu, Ping Li
Efficient greedy coordinate descent via variable partitioning. UAI (2021)
Huang Fang, Zhenan Fan, Yifan Sun, Michael P. Friedlander
Greed Meets Sparsity: Understanding and Improving Greedy Coordinate Descent for Sparse Optimization. AISTATS (2020)
Huang Fang, Nick Harvey, Victor S. Portella, Michael P. Friedlander
Online mirror descent and dual averaging: keeping pace in the dynamic case. ICML (2020)
Huang Fang, Nicholas J. A. Harvey, Victor S. Portella, Michael P. Friedlander
Online mirror descent and dual averaging: keeping pace in the dynamic case. CoRR (2020)
Huang Fang, Minhao Cheng, Cho-Jui Hsieh, Michael P. Friedlander
Fast Training for Large-Scale One-versus-All Linear Classifiers using Tree-Structured Initialization. SDM (2019)
Huang Fang, Zhen Zhang, Yiqun Shao, Cho-Jui Hsieh
Improved Bounded Matrix Completion for Large-Scale Recommender Systems. IJCAI (2017)
Huang Fang, Minhao Cheng, Cho-Jui Hsieh
A Hyperplane-Based Algorithm for Semi-Supervised Dimension Reduction. ICDM (2017)
Xicheng Tan, Huang Fang
3D Spatial Analysis Oriented Hybrid P2P Computing. CSO (2) (2009)