Feihu Huang

According to our database, Feihu Huang authored at least 75 papers between 2015 and 2024.

Collaborative distances:

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

2024

Secure Neural Network Prediction in the Cloud-Based Open Neural Network Service.

Wen Huang, Ganglin Zhang, Yongjian Liao, Jian Peng, Feihu Huang, Julong Yang

IEEE Trans. Serv. Comput., 2024

2023

A study of BERT-based methods for formal citation identification of scientific data.

Ning Yang, Zhiqiang Zhang, Feihu Huang

Scientometrics, November, 2023

Topology augmented dynamic spatial-temporal network for passenger flow forecasting in urban rail transit.

Peiyu Yi, Feihu Huang, Jince Wang, Jian Peng

Appl. Intell., November, 2023

Gradient Descent Ascent for Minimax Problems on Riemannian Manifolds.

Feihu Huang, Shangqian Gao

IEEE Trans. Pattern Anal. Mach. Intell., July, 2023

State Causality and Adaptive Covariance Decomposition Based Time Series Forecasting.

Jince Wang, Zibo He, Tianyu Geng, Feihu Huang, Pu Gong, Peiyu Yi, Jian Peng

Sensors, January, 2023

Finding reinforced structural hole spanners in social networks via node embedding.

Mengshi Li, Feihu Huang, Jian Peng

Intell. Data Anal., 2023

Adaptive Mirror Descent Bilevel Optimization.

Feihu Huang

CoRR, 2023

Near-Optimal Decentralized Momentum Method for Nonconvex-PL Minimax Problems.

Feihu Huang, Songcan Chen

CoRR, 2023

Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization.

Feihu Huang

CoRR, 2023

On Momentum-Based Gradient Methods for Bilevel Optimization with Nonconvex Lower-Level.

Feihu Huang

CoRR, 2023

Communication-Efficient Federated Bilevel Optimization with Local and Global Lower Level Problems.

Junyi Li, Feihu Huang, Heng Huang

CoRR, 2023

FedDA: Faster Framework of Local Adaptive Gradient Methods via Restarted Dual Averaging.

Junyi Li, Feihu Huang, Heng Huang

CoRR, 2023

Self-Supervised Learning Based on Similar Users for Sequential Recommendation.

Xiaomei Shu, Jun He, Feihu Huang, Jian Peng

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2023

Communication-Efficient Federated Bilevel Optimization with Global and Local Lower Level Problems.

Junyi Li, Feihu Huang, Heng Huang

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

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

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Structural Alignment for Network Pruning through Partial Regularization.

Shangqian Gao, Zeyu Zhang, Yanfu Zhang, Feihu Huang, Heng Huang

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization.

Feihu Huang, Xidong Wu, Zhengmian Hu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Faster Adaptive Federated Learning.

Xidong Wu, Feihu Huang, Zhengmian Hu, Heng Huang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Optimization of Big Data Parallel Scheduling Based on Dynamic Clustering Scheduling Algorithm.

Fang Liu, Yanxiang He, Jing He, Xing Gao, Feihu Huang

J. Signal Process. Syst., 2022

Faster Stochastic Quasi-Newton Methods.

Qingsong Zhang, Feihu Huang, Cheng Deng, Heng Huang

IEEE Trans. Neural Networks Learn. Syst., 2022

Riemannian gradient methods for stochastic composition problems.

Feihu Huang, Shangqian Gao

Neural Networks, 2022

Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization.

Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang

J. Mach. Learn. Res., 2022

A dynamical spatial-temporal graph neural network for traffic demand prediction.

Feihu Huang, Peiyu Yi, Jince Wang, Mengshi Li, Jian Peng, Xi Xiong

Inf. Sci., 2022

Adaptive Federated Minimax Optimization with Lower complexities.

Feihu Huang

CoRR, 2022

Faster Adaptive Momentum-Based Federated Methods for Distributed Composition Optimization.

Feihu Huang

CoRR, 2022

Fast Adaptive Federated Bilevel Optimization.

Feihu Huang

CoRR, 2022

Split Time Series into Patches: Rethinking Long-term Series Forecasting with Dateformer.

Julong Young, Huiqiang Wang, Junhui Chen, Feihu Huang, Jian Peng

CoRR, 2022

Local Stochastic Bilevel Optimization with Momentum-Based Variance Reduction.

Junyi Li, Feihu Huang, Heng Huang

CoRR, 2022

Time-Series Forecasting With Shape Attention^*.

Feihu Huang, Peiyu Yi, Jince Wang, Mengshi Li, Jian Peng

Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2022

Node Information Awareness Pooling for Graph Representation Learning.

Chuan Sun, Feihu Huang, Jian Peng

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

Enhanced Bilevel Optimization via Bregman Distance.

Feihu Huang, Junyi Li, Shangqian Gao, Heng Huang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

SSA: A Content-Based Sparse Attention Mechanism.

Yang Sun, Wei Hu, Fang Liu, Feihu Huang, Yonghao Wang

Proceedings of the Knowledge Science, Engineering and Management, 2022

Classification of Heads in Multi-head Attention Mechanisms.

Feihu Huang, Min Jiang, Fang Liu, Dian Xu, Zimeng Fan, Yonghao Wang

Proceedings of the Knowledge Science, Engineering and Management, 2022

Multi-layer LSTM Parallel Optimization Based on Hardware and Software Cooperation.

Qingfeng Chen, Jing Wu, Feihu Huang, Yu Han, Qiming Zhao

Proceedings of the Knowledge Science, Engineering and Management, 2022

Intent-Aware Graph Neural Networks for Session-based Recommendation.

Haoyu Xu, Feihu Huang, Jian Peng, Wenzheng Xu

Proceedings of the International Joint Conference on Neural Networks, 2022

Deep Spatio-Temporal Method for ADHD Classification Using Resting-State fMRI.

Yuan Niu, Feihu Huang, Hui Zhou, Jian Peng

Proceedings of the 34th IEEE International Conference on Tools with Artificial Intelligence, 2022

Bregman Gradient Policy Optimization.

Feihu Huang, Shangqian Gao, Heng Huang

Proceedings of the Tenth International Conference on Learning Representations, 2022

Communication-Efficient Adam-Type Algorithms for Distributed Data Mining.

Wenhan Xian, Feihu Huang, Heng Huang

Proceedings of the IEEE International Conference on Data Mining, 2022

Fast Stochastic Recursive Momentum Methods for Imbalanced Data Mining.

Xidong Wu, Feihu Huang, Heng Huang

Proceedings of the IEEE International Conference on Data Mining, 2022

Deep Learning Feature-Based Method for FY3 Image Inpainting.

Li Feng, Feihu Huang, Yan Zhang, Jinrong Hu

Proceedings of the Artificial Intelligence and Security - 8th International Conference, 2022

Disentangled Differentiable Network Pruning.

Shangqian Gao, Feihu Huang, Yanfu Zhang, Heng Huang

Proceedings of the Computer Vision - ECCV 2022, 2022

Speformer: An Efficient Hardware-Software Cooperative Solution for Sparse Spectral Transformer.

Yang Sun, Wei Hu, Fang Liu, Min Jiang, Feihu Huang, Dian Xu

Proceedings of the 9th IEEE International Conference on Cyber Security and Cloud Computing, 2022

Modeling Learner Behavior Analysis Based on Educational Big Data and Dynamic Bayesian Network.

Fang Liu, Zimeng Fan, Feihu Huang, Yining Li, Yanxiang He, Wei Hu

Proceedings of the 8th IEEE Intl Conference on Big Data Security on Cloud, 2022

2021

STPR: A Personalized Next Point-of-Interest Recommendation Model with Spatio-Temporal Effects Based on Purpose Ranking.

Feihu Huang, Shaojie Qiao, Jian Peng, Bing Guo, Nan Han

IEEE Trans. Emerg. Top. Comput., 2021

Enhanced Bilevel Optimization via Bregman Distance.

Feihu Huang, Heng Huang

CoRR, 2021

AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization.

Feihu Huang, Heng Huang

CoRR, 2021

BiAdam: Fast Adaptive Bilevel Optimization Methods.

Feihu Huang, Heng Huang

CoRR, 2021

Compositional Federated Learning: Applications in Distributionally Robust Averaging and Meta Learning.

Feihu Huang, Junyi Li, Heng Huang

CoRR, 2021

A New Framework for Variance-Reduced Hamiltonian Monte Carlo.

Zhengmian Hu, Feihu Huang, Heng Huang

CoRR, 2021

Cosmos-Loss: A Face Representation Approach With Independent Supervision.

Feihu Huang, Menglong Yang, Xuebin Lv, Fangrui Wu

IEEE Access, 2021

A Fine-grained Graph-based Spatiotemporal Network for Bike Flow Prediction in Bike-sharing Systems.

Peiyu Yi, Feihu Huang, Jian Peng

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

A Faster Decentralized Algorithm for Nonconvex Minimax Problems.

Wenhan Xian, Feihu Huang, Yanfu Zhang, Heng Huang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Efficient Mirror Descent Ascent Methods for Nonsmooth Minimax Problems.

Feihu Huang, Xidong Wu, Heng Huang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients.

Feihu Huang, Junyi Li, Heng Huang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Optimal Underdamped Langevin MCMC Method.

Zhengmian Hu, Feihu Huang, Heng Huang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Network Pruning via Performance Maximization.

Shangqian Gao, Feihu Huang, Weidong Cai, Heng Huang

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Communication-Efficient Frank-Wolfe Algorithm for Nonconvex Decentralized Distributed Learning.

Wenhan Xian, Feihu Huang, Heng Huang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Gradient Descent Ascent for Min-Max Problems on Riemannian Manifold.

Feihu Huang, Shangqian Gao, Heng Huang

CoRR, 2020

Accelerated Zeroth-Order Momentum Methods from Mini to Minimax Optimization.

Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang

CoRR, 2020

Accelerated Stochastic Gradient-free and Projection-free Methods.

Feihu Huang, Lue Tao, Songcan Chen

Proceedings of the 37th International Conference on Machine Learning, 2020

Momentum-Based Policy Gradient Methods.

Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang

Proceedings of the 37th International Conference on Machine Learning, 2020

Social Relationship Mining Based on Student Data.

Xinzheng Wang, Bing Guo, Yan Shen, Feihu Huang

Proceedings of the EBIMCS 2020: 3rd International Conference on E-Business, 2020

Discrete Model Compression With Resource Constraint for Deep Neural Networks.

Shangqian Gao, Feihu Huang, Jian Pei, Heng Huang

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

A Bimodal Gaussian Inhomogeneous Poisson Algorithm for Bike Number Prediction in a Bike-Sharing System.

Feihu Huang, Shaojie Qiao, Jian Peng, Bing Guo

IEEE Trans. Intell. Transp. Syst., 2019

A feature learning approach for face recognition with robustness to noisy label based on top-<i>N</i> prediction.

Menglong Yang, Feihu Huang, Xuebin Lv

Neurocomputing, 2019

Nonconvex Zeroth-Order Stochastic ADMM Methods with Lower Function Query Complexity.

Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang

CoRR, 2019

Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization.

Feihu Huang, Shangqian Gao, Songcan Chen, Heng Huang

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization.

Feihu Huang, Songcan Chen, Heng Huang

Proceedings of the 36th International Conference on Machine Learning, 2019

Improve-Center: A Deep Learning Face Representation Approach.

Feihu Huang, Menglong Yang, Xuebin Lyu, Fangrui Wu

Proceedings of the Fuzzy Systems and Data Mining V, 2019

Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization.

Feihu Huang, Bin Gu, Zhouyuan Huo, Songcan Chen, Heng Huang

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Joint Estimation of Multiple Conditional Gaussian Graphical Models.

Feihu Huang, Songcan Chen, Sheng-Jun Huang

IEEE Trans. Neural Networks Learn. Syst., 2018

Learning Dynamic Conditional Gaussian Graphical Models.

Feihu Huang, Songcan Chen

IEEE Trans. Knowl. Data Eng., 2018

Multiscale overlapping blocks binarized statistical image features descriptor with flip-free distance for face verification in the wild.

Tianyu Geng, Menglong Yang, Zhisheng You, Ying Cai, Feihu Huang

Neural Comput. Appl., 2018

Mini-Batch Stochastic ADMMs for Nonconvex Nonsmooth Optimization.

Feihu Huang, Songcan Chen

CoRR, 2018

2015

Joint Learning of Multiple Sparse Matrix Gaussian Graphical Models.

Feihu Huang, Songcan Chen

IEEE Trans. Neural Networks Learn. Syst., 2015