Huang Fang

According to our database, Huang Fang authored at least 16 papers between 2009 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

MQuinE: a cure for "Z-paradox" in knowledge graph embedding models.

Yang Liu, Huang Fang, Yunfeng Cai, Mingming Sun

CoRR, 2024

2023

MLN4KB: an efficient Markov logic network engine for large-scale knowledge bases and structured logic rules.

Huang Fang, Yang Liu, Yunfeng Cai, Mingming Sun

Proceedings of the ACM Web Conference 2023, 2023

Differentiable Neuro-Symbolic Reasoning on Large-Scale Knowledge Graphs.

Shengyuan Chen, Yunfeng Cai, Huang Fang, Xiao Huang, Mingming Sun

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Improved Convergence of Differential Private SGD with Gradient Clipping.

Huang Fang, Xiaoyun Li, Chenglin Fan, Ping Li

Proceedings of the Eleventh International Conference on Learning Representations, 2023

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

A dual approach for federated learning.

Zhenan Fan, Huang Fang, Michael P. Friedlander

CoRR, 2022

Fair and efficient contribution valuation for vertical federated learning.

Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Yong Zhang

CoRR, 2022

Improving Fairness for Data Valuation in Horizontal Federated Learning.

Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Changxin Liu, Yong Zhang

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

2021

Improving Fairness for Data Valuation in Federated Learning.

Zhenan Fan, Huang Fang, Zirui Zhou, Jian Pei, Michael P. Friedlander, Changxin Liu, Yong Zhang

CoRR, 2021

Efficient greedy coordinate descent via variable partitioning.

Huang Fang, Guanhua Fang, Tan Yu, Ping Li

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Fast convergence of stochastic subgradient method under interpolation.

Huang Fang, Zhenan Fan, Michael P. Friedlander

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Greed Meets Sparsity: Understanding and Improving Greedy Coordinate Descent for Sparse Optimization.

Huang Fang, Zhenan Fan, Yifan Sun, Michael P. Friedlander

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Fast Training for Large-Scale One-versus-All Linear Classifiers using Tree-Structured Initialization.

Huang Fang, Minhao Cheng, Cho-Jui Hsieh, Michael P. Friedlander

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

2017

Improved Bounded Matrix Completion for Large-Scale Recommender Systems.

Huang Fang, Zhen Zhang, Yiqun Shao, Cho-Jui Hsieh

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

A Hyperplane-Based Algorithm for Semi-Supervised Dimension Reduction.

Huang Fang, Minhao Cheng, Cho-Jui Hsieh

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

2009

3D Spatial Analysis Oriented Hybrid P2P Computing.

Xicheng Tan, Huang Fang

Proceedings of the Second International Joint Conference on Computational Sciences and Optimization, 2009