Feihu Huang

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 90

Top Topics

Gradient Method

Face Representation

Attention Mechanism

Top Venues

IEEE Trans. Neural Networks Learn. Syst.

Publications

Feihu Huang
Optimal Hessian/Jacobian-Free Nonconvex-PL Bilevel Optimization. CoRR (2024)
Feihu Huang, Jince Wang, Peiyu Yi, Jian Peng, Xi Xiong, Yun Liu
SCSQ: A sample cooperation optimization method with sample quality for recurrent neural networks. Inf. Sci. 674 (2024)
Wen Huang, Ganglin Zhang, Yongjian Liao, Jian Peng, Feihu Huang, Julong Yang
Secure Neural Network Prediction in the Cloud-Based Open Neural Network Service. IEEE Trans. Serv. Comput. 17 (2) (2024)
Junyi Li, Feihu Huang, Heng Huang
FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization. ICLR (2024)
Feihu Huang, Xinrui Wang, Junyi Li, Songcan Chen
Adaptive Federated Minimax Optimization with Lower Complexities. AISTATS (2024)
Feihu Huang, Peiyu Yi, Shan Li, Haiwen Xu
Data Quality-based Gradient Optimization for Recurrent Neural Networks. WWW (Companion Volume) (2024)
Feihu Huang, Xidong Wu, Zhengmian Hu
AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization. AISTATS (2023)
Feihu Huang, Songcan Chen
Near-Optimal Decentralized Momentum Method for Nonconvex-PL Minimax Problems. CoRR (2023)
Junyi Li, Feihu Huang, Heng Huang
FedDA: Faster Framework of Local Adaptive Gradient Methods via Restarted Dual Averaging. CoRR (2023)
Feihu Huang
Adaptive Mirror Descent Bilevel Optimization. CoRR (2023)
Jince Wang, Zibo He, Tianyu Geng, Feihu Huang, Pu Gong, Peiyu Yi, Jian Peng
State Causality and Adaptive Covariance Decomposition Based Time Series Forecasting. Sensors 23 (2) (2023)
Junhao Huang, Ziming Wang, Jian Peng, Feihu Huang
Feature reconstruction graph convolutional network for skeleton-based action recognition. Eng. Appl. Artif. Intell. 126 (2023)
Feihu Huang
Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization. CoRR (2023)
Xiaomei Shu, Jun He, Feihu Huang, Jian Peng
Self-Supervised Learning Based on Similar Users for Sequential Recommendation. SMC (2023)
Feihu Huang, Shangqian Gao
Gradient Descent Ascent for Minimax Problems on Riemannian Manifolds. IEEE Trans. Pattern Anal. Mach. Intell. 45 (7) (2023)
Huiqiang Wang, Jian Peng, Feihu Huang, Jince Wang, Junhui Chen, Yifei Xiao
MICN: Multi-scale Local and Global Context Modeling for Long-term Series Forecasting. ICLR (2023)
Shangqian Gao, Zeyu Zhang, Yanfu Zhang, Feihu Huang, Heng Huang
Structural Alignment for Network Pruning through Partial Regularization. ICCV (2023)
Peiyu Yi, Feihu Huang, Jince Wang, Jian Peng
Topology augmented dynamic spatial-temporal network for passenger flow forecasting in urban rail transit. Appl. Intell. 53 (21) (2023)
Junyi Li, Feihu Huang, Heng Huang
Communication-Efficient Federated Bilevel Optimization with Global and Local Lower Level Problems. NeurIPS (2023)
Junyi Li, Feihu Huang, Heng Huang
Communication-Efficient Federated Bilevel Optimization with Local and Global Lower Level Problems. CoRR (2023)
Ning Yang, Zhiqiang Zhang, Feihu Huang
A study of BERT-based methods for formal citation identification of scientific data. Scientometrics 128 (11) (2023)
Xidong Wu, Feihu Huang, Zhengmian Hu, Heng Huang
Faster Adaptive Federated Learning. AAAI (2023)
Feihu Huang
On Momentum-Based Gradient Methods for Bilevel Optimization with Nonconvex Lower-Level. CoRR (2023)
Mengshi Li, Feihu Huang, Jian Peng
Finding reinforced structural hole spanners in social networks via node embedding. Intell. Data Anal. 27 (1) (2023)
Shan Li, Feihu Huang
A Node Role Embedding Method Based on Neighborhood Clustering Coefficient. DSDE (2023)
Qingfeng Chen, Jing Wu, Feihu Huang, Yu Han, Qiming Zhao
Multi-layer LSTM Parallel Optimization Based on Hardware and Software Cooperation. KSEM (2) (2022)
Feihu Huang, Shangqian Gao, Heng Huang
Bregman Gradient Policy Optimization. ICLR (2022)
Xidong Wu, Feihu Huang, Heng Huang
Fast Stochastic Recursive Momentum Methods for Imbalanced Data Mining. ICDM (2022)
Feihu Huang, Min Jiang, Fang Liu, Dian Xu, Zimeng Fan, Yonghao Wang
Classification of Heads in Multi-head Attention Mechanisms. KSEM (3) (2022)
Feihu Huang, Peiyu Yi, Jince Wang, Mengshi Li, Jian Peng
. SMC (2022)
Julong Young, Huiqiang Wang, Junhui Chen, Feihu Huang, Jian Peng
Split Time Series into Patches: Rethinking Long-term Series Forecasting with Dateformer. CoRR (2022)
Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization. J. Mach. Learn. Res. 23 (2022)
Xidong Wu, Feihu Huang, Zhengmian Hu, Heng Huang
Faster Adaptive Federated Learning. CoRR (2022)
Feihu Huang, Shangqian Gao
Riemannian gradient methods for stochastic composition problems. Neural Networks 153 (2022)
Feihu Huang
Faster Adaptive Momentum-Based Federated Methods for Distributed Composition Optimization. CoRR (2022)
Wenhan Xian, Feihu Huang, Heng Huang
Communication-Efficient Adam-Type Algorithms for Distributed Data Mining. ICDM (2022)
Qingsong Zhang, Feihu Huang, Cheng Deng, Heng Huang
Faster Stochastic Quasi-Newton Methods. IEEE Trans. Neural Networks Learn. Syst. 33 (9) (2022)
Junyi Li, Feihu Huang, Heng Huang
Local Stochastic Bilevel Optimization with Momentum-Based Variance Reduction. CoRR (2022)
Li Feng, Feihu Huang, Yan Zhang, Jinrong Hu
Deep Learning Feature-Based Method for FY3 Image Inpainting. ICAIS (1) (2022)
Chuan Sun, Feihu Huang, Jian Peng
Node Information Awareness Pooling for Graph Representation Learning. PAKDD (1) (2022)
Shangqian Gao, Feihu Huang, Yanfu Zhang, Heng Huang
Disentangled Differentiable Network Pruning. ECCV (11) (2022)
Fang Liu, Yanxiang He, Jing He, Xing Gao, Feihu Huang
Optimization of Big Data Parallel Scheduling Based on Dynamic Clustering Scheduling Algorithm. J. Signal Process. Syst. 94 (11) (2022)
Haoyu Xu, Feihu Huang, Jian Peng, Wenzheng Xu
Intent-Aware Graph Neural Networks for Session-based Recommendation. IJCNN (2022)
Feihu Huang, Peiyu Yi, Jince Wang, Mengshi Li, Jian Peng, Xi Xiong
A dynamical spatial-temporal graph neural network for traffic demand prediction. Inf. Sci. 594 (2022)
Fang Liu, Zimeng Fan, Feihu Huang, Yining Li, Yanxiang He, Wei Hu
Modeling Learner Behavior Analysis Based on Educational Big Data and Dynamic Bayesian Network. BigDataSecurity/HPSC/IDS (2022)
Yuan Niu, Feihu Huang, Hui Zhou, Jian Peng
Deep Spatio-Temporal Method for ADHD Classification Using Resting-State fMRI. ICTAI (2022)
Feihu Huang, Junyi Li, Shangqian Gao, Heng Huang
Enhanced Bilevel Optimization via Bregman Distance. NeurIPS (2022)
Feihu Huang
Fast Adaptive Federated Bilevel Optimization. CoRR (2022)
Feihu Huang
Adaptive Federated Minimax Optimization with Lower complexities. CoRR (2022)
Yang Sun, Wei Hu, Fang Liu, Feihu Huang, Yonghao Wang
SSA: A Content-Based Sparse Attention Mechanism. KSEM (3) (2022)
Wenhan Xian, Feihu Huang, Heng Huang
Communication-Efficient Adam-Type Algorithms for Distributed Data Mining. CoRR (2022)
Yang Sun, Wei Hu, Fang Liu, Min Jiang, Feihu Huang, Dian Xu
Speformer: An Efficient Hardware-Software Cooperative Solution for Sparse Spectral Transformer. CSCloud/EdgeCom (2022)
Wenhan Xian, Feihu Huang, Yanfu Zhang, Heng Huang
A Faster Decentralized Algorithm for Nonconvex Minimax Problems. NeurIPS (2021)
Feihu Huang, Junyi Li, Heng Huang
SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients. NeurIPS (2021)
Wenhan Xian, Feihu Huang, Heng Huang
Communication-Efficient Frank-Wolfe Algorithm for Nonconvex Decentralized Distributed Learning. AAAI (2021)
Feihu Huang, Heng Huang
Enhanced Bilevel Optimization via Bregman Distance. CoRR (2021)
Feihu Huang, Xidong Wu, Heng Huang
Efficient Mirror Descent Ascent Methods for Nonsmooth Minimax Problems. NeurIPS (2021)
Feihu Huang, Junyi Li, Heng Huang
Compositional Federated Learning: Applications in Distributionally Robust Averaging and Meta Learning. CoRR (2021)
Shangqian Gao, Feihu Huang, Weidong Cai, Heng Huang
Network Pruning via Performance Maximization. CVPR (2021)
Zhengmian Hu, Feihu Huang, Heng Huang
A New Framework for Variance-Reduced Hamiltonian Monte Carlo. CoRR (2021)
Feihu Huang, Shangqian Gao, Heng Huang
Bregman Gradient Policy Optimization. CoRR (2021)
Feihu Huang, Shaojie Qiao, Jian Peng, Bing Guo, Nan Han
STPR: A Personalized Next Point-of-Interest Recommendation Model with Spatio-Temporal Effects Based on Purpose Ranking. IEEE Trans. Emerg. Top. Comput. 9 (2) (2021)
Feihu Huang, Heng Huang
BiAdam: Fast Adaptive Bilevel Optimization Methods. CoRR (2021)
Zhengmian Hu, Feihu Huang, Heng Huang
Optimal Underdamped Langevin MCMC Method. NeurIPS (2021)
Feihu Huang, Menglong Yang, Xuebin Lv, Fangrui Wu
Cosmos-Loss: A Face Representation Approach With Independent Supervision. IEEE Access 9 (2021)
Feihu Huang, Heng Huang
AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization. CoRR (2021)
Feihu Huang, Junyi Li, Heng Huang
SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients. CoRR (2021)
Peiyu Yi, Feihu Huang, Jian Peng
A Fine-grained Graph-based Spatiotemporal Network for Bike Flow Prediction in Bike-sharing Systems. SDM (2021)
Feihu Huang, Lue Tao, Songcan Chen
Accelerated Stochastic Gradient-free and Projection-free Methods. ICML (2020)
Feihu Huang, Lue Tao, Songcan Chen
Accelerated Stochastic Gradient-free and Projection-free Methods. CoRR (2020)
Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
Momentum-Based Policy Gradient Methods. ICML (2020)
Feihu Huang, Shangqian Gao, Heng Huang
Gradient Descent Ascent for Min-Max Problems on Riemannian Manifold. CoRR (2020)
Shangqian Gao, Feihu Huang, Jian Pei, Heng Huang
Discrete Model Compression With Resource Constraint for Deep Neural Networks. CVPR (2020)
Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
Accelerated Zeroth-Order Momentum Methods from Mini to Minimax Optimization. CoRR (2020)
Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
Momentum-Based Policy Gradient Methods. CoRR (2020)
Xinzheng Wang, Bing Guo, Yan Shen, Feihu Huang
Social Relationship Mining Based on Student Data. EBIMCS (2020)
Feihu Huang, Songcan Chen, Heng Huang
Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization. CoRR (2020)
Feihu Huang, Shaojie Qiao, Jian Peng, Bing Guo
A Bimodal Gaussian Inhomogeneous Poisson Algorithm for Bike Number Prediction in a Bike-Sharing System. IEEE Trans. Intell. Transp. Syst. 20 (8) (2019)
Feihu Huang, Menglong Yang, Xuebin Lyu, Fangrui Wu
Improve-Center: A Deep Learning Face Representation Approach. FSDM (2019)
Menglong Yang, Feihu Huang, Xuebin Lv
prediction. Neurocomputing 330 (2019)
Feihu Huang, Bin Gu, Zhouyuan Huo, Songcan Chen, Heng Huang
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization. CoRR (2019)
Feihu Huang, Songcan Chen, Heng Huang
Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization. ICML (2019)
Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
Nonconvex Zeroth-Order Stochastic ADMM Methods with Lower Function Query Complexity. CoRR (2019)
Feihu Huang, Shangqian Gao, Songcan Chen, Heng Huang
Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization. CoRR (2019)
Feihu Huang, Bin Gu, Zhouyuan Huo, Songcan Chen, Heng Huang
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization. AAAI (2019)
Feihu Huang, Shangqian Gao, Songcan Chen, Heng Huang
Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization. IJCAI (2019)
Feihu Huang, Songcan Chen
Mini-Batch Stochastic ADMMs for Nonconvex Nonsmooth Optimization. CoRR (2018)
Feihu Huang, Songcan Chen
Learning Dynamic Conditional Gaussian Graphical Models. IEEE Trans. Knowl. Data Eng. 30 (4) (2018)
Feihu Huang, Songcan Chen, Sheng-Jun Huang
Joint Estimation of Multiple Conditional Gaussian Graphical Models. IEEE Trans. Neural Networks Learn. Syst. 29 (7) (2018)
Tianyu Geng, Menglong Yang, Zhisheng You, Ying Cai, Feihu Huang
Multiscale overlapping blocks binarized statistical image features descriptor with flip-free distance for face verification in the wild. Neural Comput. Appl. 30 (10) (2018)
Feihu Huang, Songcan Chen
Joint Learning of Multiple Sparse Matrix Gaussian Graphical Models. IEEE Trans. Neural Networks Learn. Syst. 26 (11) (2015)