Parabel-Reference-Cited by-同舟云学术

Parabel

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2018 World Wide Web Conference on World Wide Web - WWW '18
language:
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Author:

Prabhu Yashoteja¹,Kag Anil²,Harsola Shrutendra³,Agrawal Rahul³,Varma Manik⁴

Affiliation:

1. Indian Institute of Technology Delhi, New Delhi, India

2. Microsoft Research India, Bengaluru, India

3. Microsoft Bing Ads, Bengaluru, India

4. Microsoft Research India & Indian Institute of Technology Delhi, Bengaluru, India

Publisher

ACM Press

Reference42 articles.

1. R. Agrawal, A. Gupta, Y. Prabhu, and M. Varma. 2013. Multi-label Learning with Millions of Labels: Recommending Advertiser Bid Phrases for Web Pages. In WWW.

2. R. Babbar and B. Shoelkopf. 2017. DiSMEC-Distributed Sparse Machines for Extreme Multi-label Classification WSDM.

3. S. Bengio, J. Weston, and D. Grangier. 2010. Label Embedding Trees for Large Multi-class Tasks. NIPS. 163--171.

4. A. Bertoni, M. Goldwurm, J. Lin, and F. Saccà. 2012. Size Constrained Distance Clustering: Separation Properties and Some Complexity Results. Vol. 115 (2012), 125--139.

5. K. Bhatia, H. Jain, P. Kar, M. Varma, and P. Jain. 2015. Sparse Local Embeddings for Extreme Multi-label Classification NIPS.

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