Extreme Meta-Classification for Large-Scale Zero-Shot Retrieval

Author:

Yadav Sachin1ORCID,Saini Deepak2ORCID,Buvanesh Anirudh1ORCID,Paliwal Bhawna1ORCID,Dahiya Kunal3ORCID,Asokan Siddarth1ORCID,Prabhu Yashoteja1ORCID,Jiao Jian2ORCID,Varma Manik1ORCID

Affiliation:

1. Microsoft Research, Bangalore, India

2. Microsoft, Redmond, WA, USA

3. Indian Institute of Technology, Delhi, India

Publisher

ACM

Reference45 articles.

1. P. Aggarwal A. Deshpande and K. Narasimhan. 2023. SemSup-XC: Semantic Supervision for Zero and Few-shot Extreme Classification. In ICML.

2. 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.

3. P. Awasthi, N. Frank, and M. Mohri. 2020. Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks. In Proceedings of the 37th International Conference on Machine Learning, Vol. 119. 431--441. https://proceedings.mlr.press/v119/awasthi20a.html

4. R. Babbar and B. Schölkopf. 2017. DiSMEC: Distributed Sparse Machines for Extreme Multi-label Classification. In WSDM.

5. P. Bajaj, D. Campos, N. Craswell, L. Deng, J. Gao, X. Liu, R. Majumder, A. McNamara, B. Mitra, T. Nguyen, M. Rosenberg, X. Song, A. Stoica, S. Tiwary, and T. Wang. 2018. MS MARCO: A Human Generated MAchine Reading COmprehension Dataset. arxiv: 1611.09268 [cs.CL]

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