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04/21/2023
Near-Optimal Decentralized Momentum Method for Nonconvex-PL Minimax Problems
Minimax optimization plays an important role in many machine learning ta...
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03/07/2023
Enhanced Adaptive Gradient Algorithms for Nonconvex-PL Minimax Optimization
In the paper, we study a class of nonconvex nonconcave minimax optimizat...
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03/07/2023
On Momentum-Based Gradient Methods for Bilevel Optimization with Nonconvex Lower-Level
Bilevel optimization is a popular two-level hierarchical optimization, w...
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02/13/2023
Communication-Efficient Federated Bilevel Optimization with Local and Global Lower Level Problems
Bilevel Optimization has witnessed notable progress recently with new em...
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02/13/2023
FedDA: Faster Framework of Local Adaptive Gradient Methods via Restarted Dual Averaging
Federated learning (FL) is an emerging learning paradigm to tackle massi...
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12/02/2022
Faster Adaptive Federated Learning
Federated learning has attracted increasing attention with the emergence...
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11/14/2022
Adaptive Federated Minimax Optimization with Lower complexities
Federated learning is a popular distributed and privacy-preserving machi...
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11/03/2022
Faster Adaptive Momentum-Based Federated Methods for Distributed Composition Optimization
Composition optimization recently appears in many machine learning appli...
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11/02/2022
Fast Adaptive Federated Bilevel Optimization
Bilevel optimization is a popular hierarchical model in machine learning...
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10/14/2022
Communication-Efficient Adam-Type Algorithms for Distributed Data Mining
Distributed data mining is an emerging research topic to effectively and...
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07/12/2022
Split Time Series into Patches: Rethinking Long-term Series Forecasting with Dateformer
Time is one of the most significant characteristics of time-series, yet ...
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05/03/2022
Local Stochastic Bilevel Optimization with Momentum-Based Variance Reduction
Bilevel Optimization has witnessed notable progress recently with new em...
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07/26/2021
Enhanced Bilevel Optimization via Bregman Distance
Bilevel optimization has been widely applied many machine learning probl...
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06/30/2021
AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization
In the paper, we propose a class of faster adaptive gradient descent asc...
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06/23/2021
Bregman Gradient Policy Optimization
In this paper, we design a novel Bregman gradient policy optimization fr...
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06/21/2021
BiAdam: Fast Adaptive Bilevel Optimization Methods
Bilevel optimization recently has attracted increased interest in machin...
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06/21/2021
Compositional Federated Learning: Applications in Distributionally Robust Averaging and Meta Learning
In the paper, we propose an effective and efficient Compositional Federa...
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06/15/2021
SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients
Adaptive gradient methods have shown excellent performance for solving m...
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02/09/2021
A New Framework for Variance-Reduced Hamiltonian Monte Carlo
We propose a new framework of variance-reduced Hamiltonian Monte Carlo (...
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10/13/2020
Gradient Descent Ascent for Min-Max Problems on Riemannian Manifold
In the paper, we study a class of useful non-convex minimax optimization...
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08/18/2020
Accelerated Zeroth-Order Momentum Methods from Mini to Minimax Optimization
In the paper, we propose a new accelerated zeroth-order momentum (Acc-ZO...
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08/04/2020
Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization
In this paper, we propose a faster stochastic alternating direction meth...
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07/13/2020
Momentum-Based Policy Gradient Methods
In the paper, we propose a class of efficient momentum-based policy grad...
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07/30/2019
Nonconvex Zeroth-Order Stochastic ADMM Methods with Lower Function Query Complexity
Zeroth-order (gradient-free) method is a class of powerful optimization ...
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05/29/2019
Zeroth-Order Stochastic Alternating Direction Method of Multipliers for Nonconvex Nonsmooth Optimization
Alternating direction method of multipliers (ADMM) is a popular optimiza...
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02/16/2019
Faster Gradient-Free Proximal Stochastic Methods for Nonconvex Nonsmooth Optimization
Proximal gradient method has been playing an important role to solve man...
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02/08/2018
Mini-Batch Stochastic ADMMs for Nonconvex Nonsmooth Optimization
In the paper, we study the mini-batch stochastic ADMMs (alternating dire...
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04/26/2017
Linear Convergence of Accelerated Stochastic Gradient Descent for Nonconvex Nonsmooth Optimization
In this paper, we study the stochastic gradient descent (SGD) method for...
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10/10/2016
