Chaobing Song | DeepAI

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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...

0 Cheuk Yin Lin, et al. ∙

∙ 12/09/2022

Cyclic Block Coordinate Descent With Variance Reduction for Composite Nonconvex Optimization

Nonconvex optimization is central in solving many machine learning probl...

0 Xufeng Cai, et al. ∙

∙ 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 ...

0 Xufeng Cai, et al. ∙

∙ 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...

0 Jelena Diakonikolas, et al. ∙

∙ 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...

0 Chaobing Song, et al. ∙

∙ 03/07/2021

Optimistic Dual Extrapolation for Coherent Non-monotone Variational Inequalities

The optimization problems associated with training generative adversaria...

0 Chaobing Song, et al. ∙

∙ 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...

0 Chaobing Song, et al. ∙

∙ 02/26/2021

Fast Cyclic Coordinate Dual Averaging with Extrapolation for Generalized Variational Inequalities

We propose the Cyclic cOordinate Dual avEraging with extRapolation (CODE...

0 Chaobing Song, et al. ∙

∙ 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...

0 Chaobing Song, et al. ∙

∙ 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...

0 Yaodong Yu, et al. ∙

∙ 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...

0 Chaobing Song, et al. ∙

∙ 09/25/2018

Fully Implicit Online Learning

Regularized online learning is widely used in machine learning. In this ...

8 Chaobing Song, et al. ∙

∙ 04/15/2016

Bayesian linear regression with Student-t assumptions

As an automatic method of determining model complexity using the trainin...

0 Chaobing Song, et al. ∙

∙ 11/25/2015

Unifying Decision Trees Split Criteria Using Tsallis Entropy

The construction of efficient and effective decision trees remains a key...

0 Yisen Wang, et al. ∙

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