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03/28/2023
Accelerated Cyclic Coordinate Dual Averaging with Extrapolation for Composite Convex Optimization
Exploiting partial first-order information in a cyclic way is arguably t...
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12/09/2022
Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization
Nonconvex optimization is central in solving many machine learning probl...
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03/17/2022
A Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusion Problems
We study stochastic monotone inclusion problems, which widely appear in ...
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03/08/2022
A Fast Scale-Invariant Algorithm for Non-negative Least Squares with Non-negative Data
Nonnegative (linear) least square problems are a fundamental class of pr...
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11/02/2021
Coordinate Linear Variance Reduction for Generalized Linear Programming
We study a class of generalized linear programs (GLP) in a large-scale s...
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03/07/2021
Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities
The optimization problems associated with training generative adversaria...
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02/26/2021
Variance Reduction via Primal-Dual Accelerated Dual Averaging for Nonsmooth Convex Finite-Sums
We study structured nonsmooth convex finite-sum optimization that appear...
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02/26/2021
Fast Cyclic Coordinate Dual Averaging with Extrapolation for Generalized Variational Inequalities
We propose the Cyclic cOordinate Dual avEraging with extRapolation (CODE...
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06/18/2020
Stochastic Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization
In this paper, we introduce a simplified and unified method for finite-s...
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06/15/2020
Learning Diverse and Discriminative Representations via the Principle of Maximal Coding Rate Reduction
To learn intrinsic low-dimensional structures from high-dimensional data...
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06/03/2019
Towards Unified Acceleration of High-Order Algorithms under Hölder Continuity and Uniform Convexity
In this paper, through a very intuitive vanilla proximal method perspec...
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09/25/2018
Fully Implicit Online Learning
Regularized online learning is widely used in machine learning. In this ...
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04/15/2016
Bayesian linear regression with Student-t assumptions
As an automatic method of determining model complexity using the trainin...
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11/25/2015
