140 citations · 146 across the 6 of their papers we have counts for
6 papers
Anderson Accelerated Operator Splitting Methods for Convex-nonconvex Regularized Problems
Qiang Heng, Xiaoqian Liu, Eric C. Chi
Convex-nonconvex (CNC) regularization is a novel paradigm that employs a nonconvex penalty function while maintaining the convexity of the entire objective function. It has been su…
Exploring Vision-Language Models for Imbalanced Learning
Yidong Wang, Zhuohao Yu, Jindong Wang +6
Vision-Language models (VLMs) that use contrastive language-image pre-training have shown promising zero-shot classification performance. However, their performance on imbalanced d…
Robust Low-rank Tensor Decomposition with the Criterion
Qiang Heng, Eric C. Chi, Yufeng Liu
The growing prevalence of tensor data, or multiway arrays, in science and engineering applications motivates the need for tensor decompositions that are robust against outliers. In…
Proximal MCMC for Bayesian Inference of Constrained and Regularized Estimation
Xinkai Zhou, Qiang Heng, Eric C. Chi +1
This paper advocates proximal Markov Chain Monte Carlo (ProxMCMC) as a flexible and general Bayesian inference framework for constrained or regularized estimation. Originally intro…
FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning
Yidong Wang, Hao Chen, Qiang Heng +9
Semi-supervised Learning (SSL) has witnessed great success owing to the impressive performances brought by various methods based on pseudo labeling and consistency regularization.…
Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo
Qiang Heng, Hua Zhou, Eric C. Chi
Proximal Markov Chain Monte Carlo is a novel construct that lies at the intersection of Bayesian computation and convex optimization, which helped popularize the use of nondifferen…