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Efficiency-Effectiveness Trade-Offs in Machine Learned Models for Information Retrieval

Published:27 June 2018Publication History

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References

  1. R.-C. Chen, L. Gallagher, R. Blanco, and J. Culpepper. 2017. Efficient Cost-Aware Cascade Ranking in Multi-Stage Retrieval Proc. SIGIR. 445--454. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. B. Mitra, F. Diaz, o, and N. Craswell. 2017. Learning to Match Using Local and Distributed Representations of Text for Web Search Proc. WWW. 1291--1299. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Y. Tsuruoka, J. Tsujii, and S. Ananiadou. 2009. Stochastic Gradient Descent Training for L1-regularized Log-linear Models with Cumulative Penalty. In Proc. AFNLP. 477--485. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. L. Wang, J. Lin, and D. Metzler. 2011. A Cascade Ranking Model for Efficient Ranked Retrieval Proc. SIGIR. 105--114. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Efficiency-Effectiveness Trade-Offs in Machine Learned Models for Information Retrieval

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          • Published in

            cover image ACM Conferences
            SIGIR '18: The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval
            June 2018
            1509 pages
            ISBN:9781450356572
            DOI:10.1145/3209978

            Copyright © 2018 Owner/Author

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            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 27 June 2018

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            SIGIR '18 Paper Acceptance Rate86of409submissions,21%Overall Acceptance Rate792of3,983submissions,20%
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