Feihu Huang
31 papers · 2019–2025 · 10 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (29) π Conference Polyglot Β· Gold π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Dynamic Duo
(21)
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Keyword Champion
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Deep Specialist
(23)
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Conference Pioneer
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Unstoppable Β· Bronze
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Prolific Year Β· Productive
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Century Club Β· Bronze
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Keyword Collector
(109)
Venues
Top co-authors
Research topics
Machine Learning
(29)
Optimization & Theory Β· Machine Learning
(27)
Mathematics & Optimization
(14)
Optimization
(14)
Deep Learning
(8)
Application Areas
(7)
Artificial Intelligence
(5)
Optimization & Theory Β· Deep Learning
(5)
Learning Paradigms Β· Machine Learning
(4)
Architectures
(3)
Learning Paradigms Β· Artificial Intelligence
(3)
Reinforcement Learning
(2)
Core AI
(2)
Methods
(2)
Bayesian & Probabilistic
(1)
Keywords
variance reduction
(12)
non-convex optimization
(7)
stochastic optimization
(7)
minimax optimization
(7)
gradient complexity
(6)
federated learning
(5)
bilevel optimization
(5)
sample complexity
(5)
channel pruning
(4)
stochastic gradient
(3)
zeroth-order optimization
(3)
adaptive learning rate
(3)
convergence rate
(3)
model compression
(3)
convolutional neural network
(3)
communication efficiency
(3)
network pruning
(2)
communication complexity
(2)
alternating direction method of multiplier
(2)
mirror descent
(2)
Papers
Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization
AISTATS 2025
Escaping Saddle Point Efficiently in Minimax and Bilevel Optimizations
IJCAI 2025
Faster Double Adaptive Gradient Methods
AAAI 2025
Generalized Smooth Bilevel Optimization with Nonconvex Lower-Level
ICML 2025
Improving Federated Domain Generalization Through Dynamical Weights Calculated from Data Influences on Global Model Update
AAAI 2025
Adaptive Federated Minimax Optimization with Lower Complexities
AISTATS 2024
BilevelPruning: Unified Dynamic and Static Channel Pruning for Convolutional Neural Networks
CVPR 2024
Faster Adaptive Decentralized Learning Algorithms
ICML 2024
FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization
ICLR 2024
Optimal Hessian/Jacobian-Free Nonconvex-PL Bilevel Optimization
ICML 2024
AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization
AISTATS 2023
Communication-Efficient Federated Bilevel Optimization with Global and Local Lower Level Problems
NeurIPS 2023
Faster Adaptive Federated Learning
AAAI 2023
MICN: Multi-scale Local and Global Context Modeling for Long-term Series Forecasting
ICLR 2023
Structural Alignment for Network Pruning through Partial Regularization
ICCV 2023
Accelerated Zeroth-Order and First-Order Momentum Methods from Mini to Minimax Optimization
JMLR 2022
Bregman Gradient Policy Optimization
ICLR 2022
Disentangled Differentiable Network Pruning
ECCV 2022
Enhanced Bilevel Optimization via Bregman Distance
NeurIPS 2022
A Faster Decentralized Algorithm for Nonconvex Minimax Problems
NeurIPS 2021
Communication-Efficient Frank-Wolfe Algorithm for Nonconvex Decentralized Distributed Learning
AAAI 2021
Efficient Mirror Descent Ascent Methods for Nonsmooth Minimax Problems
NeurIPS 2021
Network Pruning via Performance Maximization
CVPR 2021
Optimal Underdamped Langevin MCMC Method
NeurIPS 2021
SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients
NeurIPS 2021
Accelerated Stochastic Gradient-free and Projection-free Methods
ICML 2020
Discrete Model Compression With Resource Constraint for Deep Neural Networks
CVPR 2020
Momentum-Based Policy Gradient Methods
ICML 2020
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization
AAAI 2019
Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization
ICML 2019
Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization
IJCAI 2019