On Missing Labels, Long-tails and Propensities in Extreme Multi-label Classification-Reference-Cited by-同舟云学术

On Missing Labels, Long-tails and Propensities in Extreme Multi-label Classification

Published:2022-08-14 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Schultheis Erik¹,Wydmuch Marek²,Babbar Rohit¹,Dembczynski Krzysztof³

Affiliation:

1. Aalto University, Helsinki, Finland

2. Poznan University of Technology, Poznan, Poland

3. Yahoo! Research & Poznan University of Technology, New York, NY, USA

Funder

Academy of Finland

Poznan Supercomputing and Networking Center

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3534678.3539466

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3. Rohit Babbar and Bernhard Schölkopf . 2019. Data scarcity, robustness and extreme multi-label classification. Machine Learning 108 (09 2019 ). Rohit Babbar and Bernhard Schölkopf. 2019. Data scarcity, robustness and extreme multi-label classification. Machine Learning 108 (09 2019).

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5. Learning from positive and unlabeled data: a survey

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