Deep Extreme Multi-label Learning-Reference-Cited by-同舟云学术

Deep Extreme Multi-label Learning

Published:2018-06-05 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2018 ACM on International Conference on Multimedia Retrieval
language:
Short-container-title:

Author:

Zhang Wenjie¹,Yan Junchi²,Wang Xiangfeng¹,Zha Hongyuan¹

Affiliation:

1. East China Normal University, Shanghai, China

2. Shanghai Jiao Tong University, Shanghai, China

Funder

NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Information

Key Program of Shanghai Science and Technology Commission

NSCF

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3206025.3206030

Reference36 articles.

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2. Rohit Babbar and Bernhard Schölkopf. 2017. DiSMEC: Distributed Sparse Machines for Extreme Multi-label Classification WSDM. 10.1145/3018661.3018741 Rohit Babbar and Bernhard Schölkopf. 2017. DiSMEC: Distributed Sparse Machines for Extreme Multi-label Classification WSDM. 10.1145/3018661.3018741

3. Krishnakumar Balasubramanian and Guy Lebanon. 2012. The landmark selection method for multiple output prediction ICML. Krishnakumar Balasubramanian and Guy Lebanon. 2012. The landmark selection method for multiple output prediction ICML.

4. Kush Bhatia Himanshu Jain Purushottam Kar Prateek Jain and Manik Varma. 2015. Sparse Local Embeddings for Extreme Multi-label Classification NIPS. Kush Bhatia Himanshu Jain Purushottam Kar Prateek Jain and Manik Varma. 2015. Sparse Local Embeddings for Extreme Multi-label Classification NIPS.

5. Wei Bi and James T Kwok. 2011. Multi-label classification on tree-and dag-structured hierarchies ICML. Wei Bi and James T Kwok. 2011. Multi-label classification on tree-and dag-structured hierarchies ICML.

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