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Feihu Huang
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Journal Articles
- 2024
- [j21]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: 120730 (2024) - [j20]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): 659-673 (2024) - 2023
- [j19]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): 24655-24670 (2023) - [j18]Junhao Huang, Ziming Wang, Jian Peng, Feihu Huang:
Feature reconstruction graph convolutional network for skeleton-based action recognition. Eng. Appl. Artif. Intell. 126: 106855 (2023) - [j17]Mengshi Li, Feihu Huang, Jian Peng:
Finding reinforced structural hole spanners in social networks via node embedding. Intell. Data Anal. 27(1): 297-318 (2023) - [j16]Feihu Huang
, Shangqian Gao:
Gradient Descent Ascent for Minimax Problems on Riemannian Manifolds. IEEE Trans. Pattern Anal. Mach. Intell. 45(7): 8466-8476 (2023) - [j15]Ning Yang
, Zhiqiang Zhang, Feihu Huang:
A study of BERT-based methods for formal citation identification of scientific data. Scientometrics 128(11): 5865-5881 (2023) - [j14]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): 809 (2023) - 2022
- [j13]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: 286-304 (2022) - [j12]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: 36:1-36:70 (2022) - [j11]Feihu Huang
, Shangqian Gao:
Riemannian gradient methods for stochastic composition problems. Neural Networks 153: 224-234 (2022) - [j10]Qingsong Zhang
, Feihu Huang
, Cheng Deng
, Heng Huang
:
Faster Stochastic Quasi-Newton Methods. IEEE Trans. Neural Networks Learn. Syst. 33(9): 4388-4397 (2022) - [j9]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): 1243-1251 (2022) - 2021
- [j8]Feihu Huang
, Menglong Yang
, Xuebin Lv, Fangrui Wu
:
Cosmos-Loss: A Face Representation Approach With Independent Supervision. IEEE Access 9: 36819-36826 (2021) - [j7]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): 994-1005 (2021) - 2019
- [j6]Menglong Yang, Feihu Huang, Xuebin Lv:
A feature learning approach for face recognition with robustness to noisy label based on top-N prediction. Neurocomputing 330: 48-55 (2019) - [j5]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): 2848-2857 (2019) - 2018
- [j4]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): 3243-3252 (2018) - [j3]Feihu Huang
, Songcan Chen
:
Learning Dynamic Conditional Gaussian Graphical Models. IEEE Trans. Knowl. Data Eng. 30(4): 703-716 (2018) - [j2]Feihu Huang, Songcan Chen
, Sheng-Jun Huang:
Joint Estimation of Multiple Conditional Gaussian Graphical Models. IEEE Trans. Neural Networks Learn. Syst. 29(7): 3034-3046 (2018) - 2015
- [j1]Feihu Huang, Songcan Chen:
Joint Learning of Multiple Sparse Matrix Gaussian Graphical Models. IEEE Trans. Neural Networks Learn. Syst. 26(11): 2606-2620 (2015)
Conference and Workshop Papers
- 2024
- [c40]Feihu Huang, Xinrui Wang, Junyi Li, Songcan Chen:
Adaptive Federated Minimax Optimization with Lower Complexities. AISTATS 2024: 4663-4671 - [c39]Junyi Li, Feihu Huang, Heng Huang:
FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization. ICLR 2024 - [c38]Feihu Huang
, Peiyu Yi
, Shan Li
, Haiwen Xu
:
Data Quality-based Gradient Optimization for Recurrent Neural Networks. WWW (Companion Volume) 2024: 1496-1501 - 2023
- [c37]Xidong Wu, Feihu Huang, Zhengmian Hu, Heng Huang:
Faster Adaptive Federated Learning. AAAI 2023: 10379-10387 - [c36]Feihu Huang, Xidong Wu, Zhengmian Hu:
AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization. AISTATS 2023: 2365-2389 - [c35]Shan Li, Feihu Huang:
A Node Role Embedding Method Based on Neighborhood Clustering Coefficient. DSDE 2023: 1-5 - [c34]Shangqian Gao, Zeyu Zhang, Yanfu Zhang, Feihu Huang, Heng Huang:
Structural Alignment for Network Pruning through Partial Regularization. ICCV 2023: 17356-17366 - [c33]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 - [c32]Junyi Li, Feihu Huang, Heng Huang:
Communication-Efficient Federated Bilevel Optimization with Global and Local Lower Level Problems. NeurIPS 2023 - [c31]Xiaomei Shu, Jun He, Feihu Huang, Jian Peng:
Self-Supervised Learning Based on Similar Users for Sequential Recommendation. SMC 2023: 1678-1683 - 2022
- [c30]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: 48-53 - [c29]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: 180-185 - [c28]Shangqian Gao
, Feihu Huang
, Yanfu Zhang
, Heng Huang
:
Disentangled Differentiable Network Pruning. ECCV (11) 2022: 328-345 - [c27]Li Feng, Feihu Huang, Yan Zhang, Jinrong Hu:
Deep Learning Feature-Based Method for FY3 Image Inpainting. ICAIS (1) 2022: 251-263 - [c26]Xidong Wu, Feihu Huang, Heng Huang:
Fast Stochastic Recursive Momentum Methods for Imbalanced Data Mining. ICDM 2022: 578-587 - [c25]Wenhan Xian, Feihu Huang, Heng Huang:
Communication-Efficient Adam-Type Algorithms for Distributed Data Mining. ICDM 2022: 1245-1250 - [c24]Feihu Huang, Shangqian Gao, Heng Huang:
Bregman Gradient Policy Optimization. ICLR 2022 - [c23]Yuan Niu, Feihu Huang, Hui Zhou, Jian Peng:
Deep Spatio-Temporal Method for ADHD Classification Using Resting-State fMRI. ICTAI 2022: 1082-1087 - [c22]Haoyu Xu, Feihu Huang, Jian Peng, Wenzheng Xu:
Intent-Aware Graph Neural Networks for Session-based Recommendation. IJCNN 2022: 1-8 - [c21]Yang Sun
, Wei Hu
, Fang Liu
, Feihu Huang, Yonghao Wang
:
SSA: A Content-Based Sparse Attention Mechanism. KSEM (3) 2022: 669-680 - [c20]Qingfeng Chen, Jing Wu, Feihu Huang, Yu Han, Qiming Zhao:
Multi-layer LSTM Parallel Optimization Based on Hardware and Software Cooperation. KSEM (2) 2022: 681-693 - [c19]Feihu Huang
, Min Jiang
, Fang Liu
, Dian Xu
, Zimeng Fan
, Yonghao Wang
:
Classification of Heads in Multi-head Attention Mechanisms. KSEM (3) 2022: 681-692 - [c18]Feihu Huang, Junyi Li, Shangqian Gao, Heng Huang:
Enhanced Bilevel Optimization via Bregman Distance. NeurIPS 2022 - [c17]Chuan Sun, Feihu Huang, Jian Peng:
Node Information Awareness Pooling for Graph Representation Learning. PAKDD (1) 2022: 182-193 - [c16]Feihu Huang, Peiyu Yi, Jince Wang, Mengshi Li, Jian Peng:
Time-Series Forecasting With Shape Attention*. SMC 2022: 3299-3304 - 2021
- [c15]Wenhan Xian, Feihu Huang, Heng Huang:
Communication-Efficient Frank-Wolfe Algorithm for Nonconvex Decentralized Distributed Learning. AAAI 2021: 10405-10413 - [c14]Shangqian Gao, Feihu Huang, Weidong Cai
, Heng Huang:
Network Pruning via Performance Maximization. CVPR 2021: 9270-9280 - [c13]Feihu Huang, Junyi Li, Heng Huang:
SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients. NeurIPS 2021: 9074-9085 - [c12]Feihu Huang, Xidong Wu, Heng Huang:
Efficient Mirror Descent Ascent Methods for Nonsmooth Minimax Problems. NeurIPS 2021: 10431-10443 - [c11]Zhengmian Hu, Feihu Huang, Heng Huang:
Optimal Underdamped Langevin MCMC Method. NeurIPS 2021: 19363-19374 - [c10]Wenhan Xian, Feihu Huang, Yanfu Zhang, Heng Huang:
A Faster Decentralized Algorithm for Nonconvex Minimax Problems. NeurIPS 2021: 25865-25877 - [c9]Peiyu Yi
, Feihu Huang, Jian Peng:
A Fine-grained Graph-based Spatiotemporal Network for Bike Flow Prediction in Bike-sharing Systems. SDM 2021: 513-521 - 2020
- [c8]Shangqian Gao, Feihu Huang, Jian Pei
, Heng Huang:
Discrete Model Compression With Resource Constraint for Deep Neural Networks. CVPR 2020: 1896-1905 - [c7]Xinzheng Wang
, Bing Guo, Yan Shen, Feihu Huang:
Social Relationship Mining Based on Student Data. EBIMCS 2020: 573-581 - [c6]Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang:
Momentum-Based Policy Gradient Methods. ICML 2020: 4422-4433 - [c5]Feihu Huang, Lue Tao, Songcan Chen:
Accelerated Stochastic Gradient-free and Projection-free Methods. ICML 2020: 4519-4530 - 2019
- [c4]Feihu Huang, Bin Gu, Zhouyuan Huo, Songcan Chen, Heng Huang:
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization. AAAI 2019: 1503-1510 - [c3]Feihu Huang, Menglong Yang, Xuebin Lyu, Fangrui Wu:
Improve-Center: A Deep Learning Face Representation Approach. FSDM 2019: 99-105 - [c2]Feihu Huang, Songcan Chen, Heng Huang:
Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization. ICML 2019: 2839-2848 - [c1]Feihu Huang, Shangqian Gao, Songcan Chen, Heng Huang:
Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization. IJCAI 2019: 2549-2555
Informal and Other Publications
- 2024
- [i30]Feihu Huang:
Optimal Hessian/Jacobian-Free Nonconvex-PL Bilevel Optimization. CoRR abs/2407.17823 (2024) - 2023
- [i29]Junyi Li, Feihu Huang, Heng Huang:
FedDA: Faster Framework of Local Adaptive Gradient Methods via Restarted Dual Averaging. CoRR abs/2302.06103 (2023) - [i28]Junyi Li, Feihu Huang, Heng Huang:
Communication-Efficient Federated Bilevel Optimization with Local and Global Lower Level Problems. CoRR abs/2302.06701 (2023) - [i27]Feihu Huang:
On Momentum-Based Gradient Methods for Bilevel Optimization with Nonconvex Lower-Level. CoRR abs/2303.03944 (2023) - [i26]Feihu Huang:
Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization. CoRR abs/2303.03984 (2023) - [i25]Feihu Huang, Songcan Chen:
Near-Optimal Decentralized Momentum Method for Nonconvex-PL Minimax Problems. CoRR abs/2304.10902 (2023) - [i24]Feihu Huang:
Adaptive Mirror Descent Bilevel Optimization. CoRR abs/2311.04520 (2023) - 2022
- [i23]Junyi Li, Feihu Huang, Heng Huang:
Local Stochastic Bilevel Optimization with Momentum-Based Variance Reduction. CoRR abs/2205.01608 (2022) - [i22]Julong Young, Huiqiang Wang, Junhui Chen, Feihu Huang, Jian Peng:
Split Time Series into Patches: Rethinking Long-term Series Forecasting with Dateformer. CoRR abs/2207.05397 (2022) - [i21]Wenhan Xian, Feihu Huang, Heng Huang:
Communication-Efficient Adam-Type Algorithms for Distributed Data Mining. CoRR abs/2210.07454 (2022) - [i20]Feihu Huang:
Fast Adaptive Federated Bilevel Optimization. CoRR abs/2211.01122 (2022) - [i19]Feihu Huang:
Faster Adaptive Momentum-Based Federated Methods for Distributed Composition Optimization. CoRR abs/2211.01883 (2022) - [i18]Feihu Huang:
Adaptive Federated Minimax Optimization with Lower complexities. CoRR abs/2211.07303 (2022) - [i17]Xidong Wu, Feihu Huang, Zhengmian Hu, Heng Huang:
Faster Adaptive Federated Learning. CoRR abs/2212.00974 (2022) - 2021
- [i16]Zhengmian Hu, Feihu Huang, Heng Huang:
A New Framework for Variance-Reduced Hamiltonian Monte Carlo. CoRR abs/2102.04613 (2021) - [i15]Feihu Huang, Junyi Li, Heng Huang:
SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients. CoRR abs/2106.08208 (2021) - [i14]Feihu Huang, Junyi Li, Heng Huang:
Compositional Federated Learning: Applications in Distributionally Robust Averaging and Meta Learning. CoRR abs/2106.11264 (2021) - [i13]Feihu Huang, Heng Huang:
BiAdam: Fast Adaptive Bilevel Optimization Methods. CoRR abs/2106.11396 (2021) - [i12]Feihu Huang, Shangqian Gao, Heng Huang:
Bregman Gradient Policy Optimization. CoRR abs/2106.12112 (2021) - [i11]Feihu Huang, Heng Huang:
AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization. CoRR abs/2106.16101 (2021) - [i10]Feihu Huang, Heng Huang:
Enhanced Bilevel Optimization via Bregman Distance. CoRR abs/2107.12301 (2021) - 2020
- [i9]Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang:
Momentum-Based Policy Gradient Methods. CoRR abs/2007.06680 (2020) - [i8]Feihu Huang, Lue Tao, Songcan Chen:
Accelerated Stochastic Gradient-free and Projection-free Methods. CoRR abs/2007.12625 (2020) - [i7]Feihu Huang, Songcan Chen, Heng Huang:
Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization. CoRR abs/2008.01296 (2020) - [i6]Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang:
Accelerated Zeroth-Order Momentum Methods from Mini to Minimax Optimization. CoRR abs/2008.08170 (2020) - [i5]Feihu Huang, Shangqian Gao, Heng Huang:
Gradient Descent Ascent for Min-Max Problems on Riemannian Manifold. CoRR abs/2010.06097 (2020) - 2019
- [i4]Feihu Huang, Bin Gu, Zhouyuan Huo, Songcan Chen, Heng Huang:
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization. CoRR abs/1902.06158 (2019) - [i3]Feihu Huang, Shangqian Gao, Songcan Chen, Heng Huang:
Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization. CoRR abs/1905.12729 (2019) - [i2]Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang:
Nonconvex Zeroth-Order Stochastic ADMM Methods with Lower Function Query Complexity. CoRR abs/1907.13463 (2019) - 2018
- [i1]Feihu Huang, Songcan Chen:
Mini-Batch Stochastic ADMMs for Nonconvex Nonsmooth Optimization. CoRR abs/1802.03284 (2018)
Coauthor Index
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last updated on 2024-08-25 19:09 CEST by the dblp team
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