Web: http://arxiv.org/abs/2202.12387

Sept. 22, 2022, 1:13 a.m. | Zhuoning Yuan, Yuexin Wu, Zi-Hao Qiu, Xianzhi Du, Lijun Zhang, Denny Zhou, Tianbao Yang

stat.ML updates on arXiv.org arxiv.org

In this paper, we study contrastive learning from an optimization
perspective, aiming to analyze and address a fundamental issue of existing
contrastive learning methods that either rely on a large batch size or a large
dictionary of feature vectors. We consider a global objective for contrastive
learning, which contrasts each positive pair with all negative pairs for an
anchor point. From the optimization perspective, we explain why existing
methods such as SimCLR require a large batch size in order to …

arxiv global optimization performance small stochastic

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