← Search

Beitong Zhou

2 accepted papers

2023

HyperMatch: Noise-Tolerant Semi-Supervised Learning via Relaxed Contrastive Constraint

CVPR 2023poster

Recent developments of the application of Contrastive Learning in Semi-Supervised Learning (SSL) have demonstrated significant advancements, as a result of its exceptional ability to learn class-aware cluster representations and the full exploitation of massive unlabeled data. However, mismatched in…

Cited by 10SourcePDFScholar
2020

pbSGD: Powered Stochastic Gradient Descent Methods for Accelerated Non-Convex Optimization

IJCAI 2020poster

We propose a novel technique for improving the stochastic gradient descent (SGD) method to train deep networks, which we term pbSGD. The proposed pbSGD method simply raises the stochastic gradient to a certain power elementwise during iterations and introduces only one additional parameter, namely,…