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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 36 / No. 2: AAAI-22 Technical Tracks 2

Learning from Label Proportions with Prototypical Contrastive Clustering

February 1, 2023

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Authors

Laura Elena Cué La Rosa

Electrical Engineering Department, Pontifical Catholic University of Rio de Janeiro, Brazil


Dário Augusto Borges Oliveira

Data Science in Earth Observation, Technical University of Munich (TUM), Germany


DOI:

10.1609/aaai.v36i2.20112


Abstract:

The use of priors to avoid manual labeling for training machine learning methods has received much attention in the last few years. One of the critical subthemes in this regard is Learning from Label Proportions (LLP), where only the information about class proportions is available for training the models. While various LLP training settings verse in the literature, most approaches focus on bag-level label proportions errors, often leading to suboptimal solutions. This paper proposes a new model that jointly uses prototypical contrastive learning and bag-level cluster proportions to implement efficient LLP classification. Our proposal explicitly relaxes the equipartition constraint commonly used in prototypical contrastive learning methods and incorporates the exact cluster proportions into the optimal transport algorithm used for cluster assignments. At inference time, we compute the clusters' assignment, delivering instance-level classification. We experimented with our method on two widely used image classification benchmarks and report a new state-of-art LLP performance, achieving results close to fully supervised methods.

Topics: AAAI

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HOW TO CITE:

Laura Elena Cué La Rosa||Dário Augusto Borges Oliveira Learning from Label Proportions with Prototypical Contrastive Clustering Proceedings of the AAAI Conference on Artificial Intelligence (2022) 2153-2161.

Laura Elena Cué La Rosa||Dário Augusto Borges Oliveira Learning from Label Proportions with Prototypical Contrastive Clustering AAAI 2022, 2153-2161.

Laura Elena Cué La Rosa||Dário Augusto Borges Oliveira (2022). Learning from Label Proportions with Prototypical Contrastive Clustering. Proceedings of the AAAI Conference on Artificial Intelligence, 2153-2161.

Laura Elena Cué La Rosa||Dário Augusto Borges Oliveira. Learning from Label Proportions with Prototypical Contrastive Clustering. Proceedings of the AAAI Conference on Artificial Intelligence 2022 p.2153-2161.

Laura Elena Cué La Rosa||Dário Augusto Borges Oliveira. 2022. Learning from Label Proportions with Prototypical Contrastive Clustering. "Proceedings of the AAAI Conference on Artificial Intelligence". 2153-2161.

Laura Elena Cué La Rosa||Dário Augusto Borges Oliveira. (2022) "Learning from Label Proportions with Prototypical Contrastive Clustering", Proceedings of the AAAI Conference on Artificial Intelligence, p.2153-2161

Laura Elena Cué La Rosa||Dário Augusto Borges Oliveira, "Learning from Label Proportions with Prototypical Contrastive Clustering", AAAI, p.2153-2161, 2022.

Laura Elena Cué La Rosa||Dário Augusto Borges Oliveira. "Learning from Label Proportions with Prototypical Contrastive Clustering". Proceedings of the AAAI Conference on Artificial Intelligence, 2022, p.2153-2161.

Laura Elena Cué La Rosa||Dário Augusto Borges Oliveira. "Learning from Label Proportions with Prototypical Contrastive Clustering". Proceedings of the AAAI Conference on Artificial Intelligence, (2022): 2153-2161.

Laura Elena Cué La Rosa||Dário Augusto Borges Oliveira. Learning from Label Proportions with Prototypical Contrastive Clustering. AAAI[Internet]. 2022[cited 2023]; 2153-2161.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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