Feihu Huang - RankMe

69 papers A* 26A 3Journal 39Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	HomeAdam: Adam and AdamW Algorithms Sometimes Go Home to Obtain Better Provable Generalization. CoRR Feihu Huang, Guanyi Zhang, Songcan Chen
2025	A	`conf`	Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization. AISTATS Feihu Huang, Chunyu Xuan, Xinrui Wang, Siqi Zhang, Songcan Chen
2025	A*	`conf`	Escaping Saddle Point Efficiently in Minimax and Bilevel Optimizations. IJCAI Wenhan Xian, Feihu Huang, Heng Huang
2025	A*	`conf`	Faster Double Adaptive Gradient Methods. AAAI Feihu Huang, Yuning Luo
2025	A*	`conf`	Generalized Smooth Bilevel Optimization with Nonconvex Lower-Level. ICML Siqi Zhang, Xing Huang, Feihu Huang
2025	J	`jnl`	LiMuon: Light and Fast Muon Optimizer for Large Models. CoRR Feihu Huang, Yuning Luo, Songcan Chen
2024	A	`conf`	Adaptive Federated Minimax Optimization with Lower Complexities. AISTATS Feihu Huang, Xinrui Wang, Junyi Li, Songcan Chen
2024	A*	`conf`	BilevelPruning: Unified Dynamic and Static Channel Pruning for Convolutional Neural Networks. CVPR Shangqian Gao, Yanfu Zhang, Feihu Huang, Heng Huang
2024	A*	`conf`	Faster Adaptive Decentralized Learning Algorithms. ICML Feihu Huang, Jianyu Zhao
2024	J	`jnl`	Faster Adaptive Decentralized Learning Algorithms. CoRR Feihu Huang, Jianyu Zhao
2024	A*	`conf`	FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization. ICLR Junyi Li, Feihu Huang, Heng Huang
2024	A*	`conf`	Optimal Hessian/Jacobian-Free Nonconvex-PL Bilevel Optimization. ICML Feihu Huang
2024	J	`jnl`	Optimal Hessian/Jacobian-Free Nonconvex-PL Bilevel Optimization. CoRR Feihu Huang
2023	A	`conf`	AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization. AISTATS Feihu Huang, Xidong Wu, Zhengmian Hu
2023	J	`jnl`	Adaptive Mirror Descent Bilevel Optimization. CoRR Feihu Huang
2023	A*	`conf`	Communication-Efficient Federated Bilevel Optimization with Global and Local Lower Level Problems. NeurIPS Junyi Li, Feihu Huang, Heng Huang
2023	J	`jnl`	Communication-Efficient Federated Bilevel Optimization with Local and Global Lower Level Problems. CoRR Junyi Li, Feihu Huang, Heng Huang
2023	J	`jnl`	Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization. CoRR Feihu Huang
2023	A*	`conf`	Faster Adaptive Federated Learning. AAAI Xidong Wu, Feihu Huang, Zhengmian Hu, Heng Huang
2023	J	`jnl`	FedDA: Faster Framework of Local Adaptive Gradient Methods via Restarted Dual Averaging. CoRR Junyi Li, Feihu Huang, Heng Huang
2023	J	`jnl`	Gradient Descent Ascent for Minimax Problems on Riemannian Manifolds. IEEE Trans. Pattern Anal. Mach. Intell. Feihu Huang, Shangqian Gao
2023	J	`jnl`	Near-Optimal Decentralized Momentum Method for Nonconvex-PL Minimax Problems. CoRR Feihu Huang, Songcan Chen
2023	J	`jnl`	On Momentum-Based Gradient Methods for Bilevel Optimization with Nonconvex Lower-Level. CoRR Feihu Huang
2023	A*	`conf`	Structural Alignment for Network Pruning through Partial Regularization. ICCV Shangqian Gao, Zeyu Zhang, Yanfu Zhang, Feihu Huang, Heng Huang
2022	J	`jnl`	Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization. J. Mach. Learn. Res. Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
2022	J	`jnl`	Adaptive Federated Minimax Optimization with Lower complexities. CoRR Feihu Huang
2022	A*	`conf`	Bregman Gradient Policy Optimization. ICLR Feihu Huang, Shangqian Gao, Heng Huang
2022	A*	`conf`	Communication-Efficient Adam-Type Algorithms for Distributed Data Mining. ICDM Wenhan Xian, Feihu Huang, Heng Huang
2022	J	`jnl`	Communication-Efficient Adam-Type Algorithms for Distributed Data Mining. CoRR Wenhan Xian, Feihu Huang, Heng Huang
2022	—	`conf`	Disentangled Differentiable Network Pruning. ECCV (11) Shangqian Gao, Feihu Huang, Yanfu Zhang, Heng Huang
2022	A*	`conf`	Enhanced Bilevel Optimization via Bregman Distance. NeurIPS Feihu Huang, Junyi Li, Shangqian Gao, Heng Huang
2022	J	`jnl`	Fast Adaptive Federated Bilevel Optimization. CoRR Feihu Huang
2022	A*	`conf`	Fast Stochastic Recursive Momentum Methods for Imbalanced Data Mining. ICDM Xidong Wu, Feihu Huang, Heng Huang
2022	J	`jnl`	Faster Adaptive Federated Learning. CoRR Xidong Wu, Feihu Huang, Zhengmian Hu, Heng Huang
2022	J	`jnl`	Faster Adaptive Momentum-Based Federated Methods for Distributed Composition Optimization. CoRR Feihu Huang
2022	J	`jnl`	Faster Stochastic Quasi-Newton Methods. IEEE Trans. Neural Networks Learn. Syst. Qingsong Zhang, Feihu Huang, Cheng Deng, Heng Huang
2022	J	`jnl`	Local Stochastic Bilevel Optimization with Momentum-Based Variance Reduction. CoRR Junyi Li, Feihu Huang, Heng Huang
2022	J	`jnl`	Riemannian gradient methods for stochastic composition problems. Neural Networks Feihu Huang, Shangqian Gao
2021	A*	`conf`	A Faster Decentralized Algorithm for Nonconvex Minimax Problems. NeurIPS Wenhan Xian, Feihu Huang, Yanfu Zhang, Heng Huang
2021	J	`jnl`	A New Framework for Variance-Reduced Hamiltonian Monte Carlo. CoRR Zhengmian Hu, Feihu Huang, Heng Huang
2021	J	`jnl`	AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization. CoRR Feihu Huang, Heng Huang
2021	J	`jnl`	BiAdam: Fast Adaptive Bilevel Optimization Methods. CoRR Feihu Huang, Heng Huang
2021	J	`jnl`	Bregman Gradient Policy Optimization. CoRR Feihu Huang, Shangqian Gao, Heng Huang
2021	A*	`conf`	Communication-Efficient Frank-Wolfe Algorithm for Nonconvex Decentralized Distributed Learning. AAAI Wenhan Xian, Feihu Huang, Heng Huang
2021	J	`jnl`	Compositional Federated Learning: Applications in Distributionally Robust Averaging and Meta Learning. CoRR Feihu Huang, Junyi Li, Heng Huang
2021	A*	`conf`	Efficient Mirror Descent Ascent Methods for Nonsmooth Minimax Problems. NeurIPS Feihu Huang, Xidong Wu, Heng Huang
2021	J	`jnl`	Enhanced Bilevel Optimization via Bregman Distance. CoRR Feihu Huang, Heng Huang
2021	A*	`conf`	Network Pruning via Performance Maximization. CVPR Shangqian Gao, Feihu Huang, Weidong Cai, Heng Huang
2021	A*	`conf`	Optimal Underdamped Langevin MCMC Method. NeurIPS Zhengmian Hu, Feihu Huang, Heng Huang
2021	A*	`conf`	SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients. NeurIPS Feihu Huang, Junyi Li, Heng Huang
2021	J	`jnl`	SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients. CoRR Feihu Huang, Junyi Li, Heng Huang
2020	A*	`conf`	Accelerated Stochastic Gradient-free and Projection-free Methods. ICML Feihu Huang, Lue Tao, Songcan Chen
2020	J	`jnl`	Accelerated Stochastic Gradient-free and Projection-free Methods. CoRR Feihu Huang, Lue Tao, Songcan Chen
2020	J	`jnl`	Accelerated Zeroth-Order Momentum Methods from Mini to Minimax Optimization. CoRR Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
2020	A*	`conf`	Discrete Model Compression With Resource Constraint for Deep Neural Networks. CVPR Shangqian Gao, Feihu Huang, Jian Pei, Heng Huang
2020	J	`jnl`	Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization. CoRR Feihu Huang, Songcan Chen, Heng Huang
2020	J	`jnl`	Gradient Descent Ascent for Min-Max Problems on Riemannian Manifold. CoRR Feihu Huang, Shangqian Gao, Heng Huang
2020	A*	`conf`	Momentum-Based Policy Gradient Methods. ICML Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
2020	J	`jnl`	Momentum-Based Policy Gradient Methods. CoRR Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
2019	A*	`conf`	Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization. AAAI Feihu Huang, Bin Gu, Zhouyuan Huo, Songcan Chen, Heng Huang
2019	J	`jnl`	Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization. CoRR Feihu Huang, Bin Gu, Zhouyuan Huo, Songcan Chen, Heng Huang
2019	A*	`conf`	Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization. ICML Feihu Huang, Songcan Chen, Heng Huang
2019	J	`jnl`	Nonconvex Zeroth-Order Stochastic ADMM Methods with Lower Function Query Complexity. CoRR Feihu Huang, Shangqian Gao, Jian Pei, Heng Huang
2019	A*	`conf`	Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization. IJCAI Feihu Huang, Shangqian Gao, Songcan Chen, Heng Huang
2019	J	`jnl`	Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization. CoRR Feihu Huang, Shangqian Gao, Songcan Chen, Heng Huang
2018	J	`jnl`	Joint Estimation of Multiple Conditional Gaussian Graphical Models. IEEE Trans. Neural Networks Learn. Syst. Feihu Huang, Songcan Chen, Sheng-Jun Huang
2018	J	`jnl`	Learning Dynamic Conditional Gaussian Graphical Models. IEEE Trans. Knowl. Data Eng. Feihu Huang, Songcan Chen
2018	J	`jnl`	Mini-Batch Stochastic ADMMs for Nonconvex Nonsmooth Optimization. CoRR Feihu Huang, Songcan Chen
2015	J	`jnl`	Joint Learning of Multiple Sparse Matrix Gaussian Graphical Models. IEEE Trans. Neural Networks Learn. Syst. Feihu Huang, Songcan Chen