Continuation methods and curriculum learning for learning to rank

Nicola Ferro; Maria Maistro; Claudio Lucchese; Raffaele Perego

doi:10.1145/3269206.3269239

Continuation methods and curriculum learning for learning to rank

Nicola Ferro, Maria Maistro, Claudio Lucchese, Raffaele Perego

4 Citations (Scopus)

Abstract

In this paper we explore the use of Continuation Methods and Curriculum Learning techniques in the area of Learning to Rank. The basic idea is to design the training process as a learning path across increasingly complex training instances and objective functions. We propose to instantiate continuation methods in Learning to Rank by changing the IR measure to optimize during training, and we present two different curriculum learning strategies to identify easy training examples. Experimental results show that simple continuation methods are more promising than curriculum learning ones since they allow for slightly improving the performance of state-of-the-art ?-MART models and provide a faster convergence speed.

Original language	English
Title of host publication	CIKM 2018 - Proceedings of the 27th ACM International Conference on Information and Knowledge Management
Editors	Norman Paton, Selcuk Candan, Haixun Wang, James Allan, Rakesh Agrawal, Alexandros Labrinidis, Alfredo Cuzzocrea, Mohammed Zaki, Divesh Srivastava, Andrei Broder, Assaf Schuster
Number of pages	4
Publisher	Association for Computing Machinery, Inc.
Publication date	17 Oct 2018
Pages	1523-1526
ISBN (Electronic)	9781450360142
DOIs	https://doi.org/10.1145/3269206.3269239
Publication status	Published - 17 Oct 2018
Externally published	Yes
Event	27th ACM International Conference on Information and Knowledge Management, CIKM 2018 - Torino, Italy Duration: 22 Oct 2018 → 26 Oct 2018

Conference

Conference	27th ACM International Conference on Information and Knowledge Management, CIKM 2018
Country/Territory	Italy
City	Torino
Period	22/10/2018 → 26/10/2018
Sponsor	ACM SIGIR, ACM SIGWEB

Keywords

Curriculum learning
Lambdamart
Learning to rank

Access to Document

10.1145/3269206.3269239

Cite this

Ferro, N., Maistro, M., Lucchese, C., & Perego, R. (2018). Continuation methods and curriculum learning for learning to rank. In N. Paton, S. Candan, H. Wang, J. Allan, R. Agrawal, A. Labrinidis, A. Cuzzocrea, M. Zaki, D. Srivastava, A. Broder, & A. Schuster (Eds.), CIKM 2018 - Proceedings of the 27th ACM International Conference on Information and Knowledge Management (pp. 1523-1526). Association for Computing Machinery, Inc.. https://doi.org/10.1145/3269206.3269239

Continuation methods and curriculum learning for learning to rank. / Ferro, Nicola; Maistro, Maria; Lucchese, Claudio et al.
CIKM 2018 - Proceedings of the 27th ACM International Conference on Information and Knowledge Management. ed. / Norman Paton; Selcuk Candan; Haixun Wang; James Allan; Rakesh Agrawal; Alexandros Labrinidis; Alfredo Cuzzocrea; Mohammed Zaki; Divesh Srivastava; Andrei Broder; Assaf Schuster. Association for Computing Machinery, Inc., 2018. p. 1523-1526.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Ferro, N, Maistro, M, Lucchese, C & Perego, R 2018, Continuation methods and curriculum learning for learning to rank. in N Paton, S Candan, H Wang, J Allan, R Agrawal, A Labrinidis, A Cuzzocrea, M Zaki, D Srivastava, A Broder & A Schuster (eds), CIKM 2018 - Proceedings of the 27th ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, Inc., pp. 1523-1526, 27th ACM International Conference on Information and Knowledge Management, CIKM 2018, Torino, Italy, 22/10/2018. https://doi.org/10.1145/3269206.3269239

Ferro N, Maistro M, Lucchese C, Perego R. Continuation methods and curriculum learning for learning to rank. In Paton N, Candan S, Wang H, Allan J, Agrawal R, Labrinidis A, Cuzzocrea A, Zaki M, Srivastava D, Broder A, Schuster A, editors, CIKM 2018 - Proceedings of the 27th ACM International Conference on Information and Knowledge Management. Association for Computing Machinery, Inc. 2018. p. 1523-1526 doi: 10.1145/3269206.3269239

Ferro, Nicola ; Maistro, Maria ; Lucchese, Claudio et al. / Continuation methods and curriculum learning for learning to rank. CIKM 2018 - Proceedings of the 27th ACM International Conference on Information and Knowledge Management. editor / Norman Paton ; Selcuk Candan ; Haixun Wang ; James Allan ; Rakesh Agrawal ; Alexandros Labrinidis ; Alfredo Cuzzocrea ; Mohammed Zaki ; Divesh Srivastava ; Andrei Broder ; Assaf Schuster. Association for Computing Machinery, Inc., 2018. pp. 1523-1526

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Continuation methods and curriculum learning for learning to rank

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Keywords

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