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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 36 / No. 8: AAAI-22 Technical Tracks 8

Max-Margin Contrastive Learning

February 1, 2023

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Authors

Anshul Shah

Johns Hopkins University, Baltimore, MD


Suvrit Sra

Massachusetts Institute of Technology, Cambridge, MA


Rama Chellappa

Johns Hopkins University, Baltimore, MD


Anoop Cherian

Mitsubishi Electric Research Labs, Cambridge, MA


DOI:

10.1609/aaai.v36i8.20796


Abstract:

Standard contrastive learning approaches usually require a large number of negatives for effective unsupervised learning and often exhibit slow convergence. We suspect this behavior is due to the suboptimal selection of negatives used for offering contrast to the positives. We counter this difficulty by taking inspiration from support vector machines (SVMs) to present max-margin contrastive learning (MMCL). Our approach selects negatives as the sparse support vectors obtained via a quadratic optimization problem, and contrastiveness is enforced by maximizing the decision margin. As SVM optimization can be computationally demanding, especially in an end-to-end setting, we present simplifications that alleviate the computational burden. We validate our approach on standard vision benchmark datasets, demonstrating better performance in unsupervised representation learning over state-of-the-art, while having better empirical convergence properties.

Topics: AAAI

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HOW TO CITE:

Anshul Shah||Suvrit Sra||Rama Chellappa||Anoop Cherian Max-Margin Contrastive Learning Proceedings of the AAAI Conference on Artificial Intelligence (2022) 8220-8230.

Anshul Shah||Suvrit Sra||Rama Chellappa||Anoop Cherian Max-Margin Contrastive Learning AAAI 2022, 8220-8230.

Anshul Shah||Suvrit Sra||Rama Chellappa||Anoop Cherian (2022). Max-Margin Contrastive Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 8220-8230.

Anshul Shah||Suvrit Sra||Rama Chellappa||Anoop Cherian. Max-Margin Contrastive Learning. Proceedings of the AAAI Conference on Artificial Intelligence 2022 p.8220-8230.

Anshul Shah||Suvrit Sra||Rama Chellappa||Anoop Cherian. 2022. Max-Margin Contrastive Learning. "Proceedings of the AAAI Conference on Artificial Intelligence". 8220-8230.

Anshul Shah||Suvrit Sra||Rama Chellappa||Anoop Cherian. (2022) "Max-Margin Contrastive Learning", Proceedings of the AAAI Conference on Artificial Intelligence, p.8220-8230

Anshul Shah||Suvrit Sra||Rama Chellappa||Anoop Cherian, "Max-Margin Contrastive Learning", AAAI, p.8220-8230, 2022.

Anshul Shah||Suvrit Sra||Rama Chellappa||Anoop Cherian. "Max-Margin Contrastive Learning". Proceedings of the AAAI Conference on Artificial Intelligence, 2022, p.8220-8230.

Anshul Shah||Suvrit Sra||Rama Chellappa||Anoop Cherian. "Max-Margin Contrastive Learning". Proceedings of the AAAI Conference on Artificial Intelligence, (2022): 8220-8230.

Anshul Shah||Suvrit Sra||Rama Chellappa||Anoop Cherian. Max-Margin Contrastive Learning. AAAI[Internet]. 2022[cited 2023]; 8220-8230.


ISSN: 2374-3468


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Copyright 2022, Association for the Advancement of
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