| 2025 | AAAI | Faster Double Adaptive Gradient Methods. | Feihu Huang, Yuning Luo |
| 2025 | AAAI | Improving Federated Domain Generalization Through Dynamical Weights Calculated from Data Influences on Global Model Update. | Zikun Zhou, Wen Huang, Xingyi Wang, Zhishuo Zhang, Zhun Zhang, Jian Peng, Feihu Huang |
| 2025 | AISTATS | Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization. | Feihu Huang, Chunyu Xuan, Xinrui Wang, Siqi Zhang, Songcan Chen |
| 2025 | ICML | Generalized Smooth Bilevel Optimization with Nonconvex Lower-Level. | Siqi Zhang, Xing Huang, Feihu Huang |
| 2025 | IJCAI | Escaping Saddle Point Efficiently in Minimax and Bilevel Optimizations. | Wenhan Xian, Feihu Huang, Heng Huang |
| 2024 | AISTATS | Adaptive Federated Minimax Optimization with Lower Complexities. | Feihu Huang, Xinrui Wang, Junyi Li, Songcan Chen |
| 2024 | CVPR | BilevelPruning: Unified Dynamic and Static Channel Pruning for Convolutional Neural Networks. | Shangqian Gao, Yanfu Zhang, Feihu Huang, Heng Huang |
| 2024 | ICLR | FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization. | Junyi Li, Feihu Huang, Heng Huang |
| 2024 | ICML | Optimal Hessian/Jacobian-Free Nonconvex-PL Bilevel Optimization. | Feihu Huang |
| 2024 | ICML | Faster Adaptive Decentralized Learning Algorithms. | Feihu Huang, Jianyu Zhao |
| 2024 | WWW | Data Quality-based Gradient Optimization for Recurrent Neural Networks. | Feihu Huang, Peiyu Yi, Shan Li, Haiwen Xu |
| 2023 | AAAI | Faster Adaptive Federated Learning. | Xidong Wu, Feihu Huang, Zhengmian Hu, Heng Huang |
| 2023 | AISTATS | AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization. | Feihu Huang, Xidong Wu, Zhengmian Hu |
| 2023 | ICCV | Structural Alignment for Network Pruning through Partial Regularization. | Shangqian Gao, Zeyu Zhang, Yanfu Zhang, Feihu Huang, Heng Huang |
| 2023 | ICLR | MICN: Multi-scale Local and Global Context Modeling for Long-term Series Forecasting. | Huiqiang Wang, Jian Peng, Feihu Huang, Jince Wang, Junhui Chen, Yifei Xiao |
| 2023 | SMC | Self-Supervised Learning Based on Similar Users for Sequential Recommendation. | Xiaomei Shu, Jun He, Feihu Huang, Jian Peng |
| 2022 | ECCV | Disentangled Differentiable Network Pruning. | Shangqian Gao, Feihu Huang, Yanfu Zhang, Heng Huang |
| 2022 | ICDM | Fast Stochastic Recursive Momentum Methods for Imbalanced Data Mining. | Xidong Wu, Feihu Huang, Heng Huang |
| 2022 | ICDM | Communication-Efficient Adam-Type Algorithms for Distributed Data Mining. | Wenhan Xian, Feihu Huang, Heng Huang |
| 2022 | ICLR | Bregman Gradient Policy Optimization. | Feihu Huang, Shangqian Gao, Heng Huang |
| 2022 | IJCNN | Intent-Aware Graph Neural Networks for Session-based Recommendation. | Haoyu Xu, Feihu Huang, Jian Peng, Wenzheng Xu |
| 2022 | ICTAI | Deep Spatio-Temporal Method for ADHD Classification Using Resting-State fMRI. | Yuan Niu, Feihu Huang, Hui Zhou, Jian Peng |
| 2022 | KSEM | Multi-layer LSTM Parallel Optimization Based on Hardware and Software Cooperation. | Qingfeng Chen, Jing Wu, Feihu Huang, Yu Han, Qiming Zhao |
| 2022 | KSEM | Classification of Heads in Multi-head Attention Mechanisms. | Feihu Huang, Min Jiang, Fang Liu, Dian Xu, Zimeng Fan, Yonghao Wang |
| 2022 | KSEM | SSA: A Content-Based Sparse Attention Mechanism. | Yang Sun, Wei Hu, Fang Liu, Feihu Huang, Yonghao Wang |
| 2022 | PAKDD | Node Information Awareness Pooling for Graph Representation Learning. | Chuan Sun, Feihu Huang, Jian Peng |
| 2022 | SMC | Time-Series Forecasting With Shape Attention | Feihu Huang, Peiyu Yi, Jince Wang, Mengshi Li, Jian Peng |
| 2021 | AAAI | Communication-Efficient Frank-Wolfe Algorithm for Nonconvex Decentralized Distributed Learning. | Wenhan Xian, Feihu Huang, Heng Huang |
| 2021 | CVPR | Network Pruning via Performance Maximization. | Shangqian Gao, Feihu Huang, Weidong Cai, Heng Huang |
| 2021 | SDM | A Fine-grained Graph-based Spatiotemporal Network for Bike Flow Prediction in Bike-sharing Systems. | Peiyu Yi, Feihu Huang, Jian Peng |
| 2020 | CVPR | Discrete Model Compression With Resource Constraint for Deep Neural Networks. | Shangqian Gao, Feihu Huang, Jian Pei, Heng Huang |
| 2020 | ICML | Momentum-Based Policy Gradient Methods. | Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang |
| 2020 | ICML | Accelerated Stochastic Gradient-free and Projection-free Methods. | Feihu Huang, Lue Tao, Songcan Chen |
| 2019 | AAAI | Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization. | Feihu Huang, Bin Gu, Zhouyuan Huo, Songcan Chen, Heng Huang |
| 2019 | ICML | Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization. | Feihu Huang, Songcan Chen, Heng Huang |
| 2019 | IJCAI | Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization. | Feihu Huang, Shangqian Gao, Songcan Chen, Heng Huang |