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Ofer Dekel (researcher)

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This article is about the Microsoft Researcher. For the Israeli lawyer and envoy, see Ofer Dekel.
Ofer Dekel
Ofer Dekel works with the application of machine learning techniques in the development of the Bing search engine.
Ofer Dekel works with the application
of machine learning techniques
in the development of Bing.
Born
Israel
Alma materHebrew University of Jerusalem
Scientific career
FieldsMachine learning, statistical learning theory, online prediction, optimization, web search, and stochastic optimization
InstitutionsMicrosoft Research
University of Washington

Ofer Dekel is a computer science researcher in the Machine Learning Department of Microsoft Research.[1] He obtained his PhD in Computer Science from the Hebrew University of Jerusalem[2] and is an affiliate faculty at the Computer Science & Engineering department at the University of Washington.[3]

Areas of research

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Dekel's research topics include machine learning, online prediction, statistical learning theory, and stochastic optimization.[3] He is currently engaged in the application of machine learning techniques in the development of the Bing search engine.[2]

Bibliography

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h-index

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As of September 2013, Ofer Dekel has an h-index of approximately 18,[4][5] above the mean for computer scientists.[6]

Highly cited publications

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Below is a select list of publications in descending order of citations

  • Crammer, Koby; Dekel, Ofer; Keshet, Joseph; Shalev-shwartz, Shai; Singer, Yoram (2006). "Online Passive-Aggressive Algorithms". Journal of Machine Learning Research. 7: 551–585. Retrieved 2013-09-12.
  • Dekel, Ofer; Manning, Christopher; Singer, Yoram (2003). Log-Linear Models for Label Ranking (PDF). Neural Information Processing Systems. Retrieved 2013-09-12.
  • Dekel, Ofer; Keshet, Joseph; Singer, Yoram (2004). Large margin hierarchical classification. International Conference on Machine Learning. doi:10.1145/1015330.1015374. Retrieved 2013-09-12.
  • Closed access icon Dekel, Ofer; Shalev-Shwartz, Shai; Singer, Yoram (2008). "The forgetron: A kernel-based perceptron on a budget". SIAM Journal on Computing. 37 (5): 1342–1372. CiteSeerX 10.1.1.115.568. doi:10.1137/060666998. (subscription required)
  • Dekel, Ofer; Shamir, Ohad (2009). Vox populi: Collecting high-quality labels from a crowd. COLT 2009. PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning. Archived from the original on 2012-06-26. Retrieved 2013-09-16.
  • Dekel, Ofer; Fischer, Felix; Procaccia, Ariel D. (December 2010). "Incentive compatible regression learning". Journal of Computer and System Sciences. 76 (8): 759–777. doi:10.1016/j.jcss.2010.03.003. S2CID 141455.
  • Closed access icon Dekel, Ofer; Keshet, Joseph; Singer, Yoram (2005). "An online algorithm for hierarchical phoneme classification". Machine Learning for Multimodal Interaction. Lecture Notes in Computer Science. Vol. 3361. Springer. pp. 146–158. CiteSeerX 10.1.1.108.8522. doi:10.1007/978-3-540-30568-2_13. ISBN 978-3-540-30568-2. OCLC 108716892. (subscription required)
  • Dekel, Ofer; Shamir, Ohad; Xiao, Lin (November 2010). "Learning to classify with missing and corrupted features". Machine learning. 81 (2): 149–178. CiteSeerX 10.1.1.187.8865. doi:10.1007/s10994-009-5124-8. S2CID 259138.
  • Dekel, Ofer; Gilad-Bachrach, Ran; Shamir, Ohad; Xiao, Lin (January 2012). "Optimal distributed online prediction using mini-batches". Journal of Machine Learning Research. 13 (1). Association for Computing Machinery: 165–202. Retrieved 2013-09-16.

See also

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References

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  1. ^ Machine Learning Department. "Machine Learning Department". Redmond, WA, USA: Microsoft Research. Retrieved August 30, 2011.
  2. ^ a b "A Tutorial on Modern Learning Theory (course description)". Retrieved 2013-09-13.
  3. ^ a b "Ofer Dekel | Computer Science & Engineering". Seattle, WA: University of Washington. Retrieved 2013-09-13.
  4. ^ "Ofer Dekel - computer science researcher". Retrieved 2013-09-20.
  5. ^ ".H-Index". Archived from the original on 2013-09-21. Retrieved 2013-09-20.
  6. ^ Franceschet, Massimo (2010). "A comparison of bibliometric indicators for computer science scholars and journals on Web of Science and Google Scholar" (PDF). Scientometrics. 83 (1): 243–258. CiteSeerX 10.1.1.169.8426. doi:10.1007/s11192-009-0021-2. ISSN 1588-2861. OCLC 4846912. S2CID 10574859. Retrieved 2013-09-20. For academics with computer science research focus, the average Google Scholar h index is 15.2, while the average h score on Scopus is 7.9 and on Web of Science (cited reference search) is 6.8.
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