Thorsten Joachims

Affiliations: 
Cornell University, Ithaca, NY, United States 
Area:
Artificial Intelligence, Computer Science
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"Thorsten Joachims"

Children

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Thomas W. Finley grad student 2009 Cornell
Benyah Shaparenko grad student 2010 Cornell
Ruben Sipos grad student 2014 Cornell
Brad Gulko grad student 2021-2017 Cornell (Computational Biology Tree)
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Publications

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Jain A, Sharma S, Joachims T, et al. (2015) Learning preferences for manipulation tasks from online coactive feedback International Journal of Robotics Research. 34: 1296-1313
Luaces O, Díez J, Joachims T, et al. (2015) Mapping preferences into Euclidean space Expert Systems With Applications. 42: 8588-8596
Díez J, Gamboa E, Cossío TGD, et al. (2015) Analysis of nutrition data by means of a matrix factorization method Progress in Artificial Intelligence. 3: 119-127
Sipos R, Ghosh A, Joachims T. (2014) Was this review helpful to you? It depends! Context and voting patterns in online content Www 2014 - Proceedings of the 23rd International Conference On World Wide Web. 337-347
Anand A, Koppula HS, Joachims T, et al. (2013) Contextually guided semantic labeling and search for three-dimensional point clouds International Journal of Robotics Research. 32: 19-34
Sipos R, Joachims T. (2013) Generating comparative summaries from reviews International Conference On Information and Knowledge Management, Proceedings. 1853-1856
Sipos R, Swaminathan A, Shivaswamy P, et al. (2012) Temporal corpus summarization using submodular word coverage Acm International Conference Proceeding Series. 754-763
Chapelle O, Joachims T, Radlinski F, et al. (2012) Large-scale validation and analysis of interleaved search evaluation Acm Transactions On Information Systems. 30
Xu Z, Kersting K, Joachims T. (2010) Fast active exploration for link-based preference learning using gaussian processes Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 6323: 499-514
Joachims T, Hofmann T, Yue Y, et al. (2009) Predicting structured objects with support vector machines Communications of the Acm. 52: 97-104
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