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Haym Hirsh
2010 – today
- 2013
[j22]Rezarta Islamaj Dogan, Yolanda Gil, Haym Hirsh, Narayanan C. Krishnan, Michael Lewis, Çetin Meriçli, Parisa Rashidi, Victor Raskin, Samarth Swarup, Wei Sun, Julia M. Taylor, Lana Yeganova: Reports on the 2012 AAAI Fall Symposium Series. AI Magazine 34(1): 93-100 (2013)- 2012
- [i2]Seyda Ertekin, Haym Hirsh, Cynthia Rudin: Learning to Predict the Wisdom of Crowds. CoRR abs/1204.3611 (2012)
- 2011
- [i1]Chumki Basu, William W. Cohen, Haym Hirsh, Craig G. Nevill-Manning: Technical Paper Recommendation: A Study in Combining Multiple Information Sources. CoRR abs/1106.0248 (2011)
2000 – 2009
- 2009
- [j21]Razvan C. Bunescu, Vitor R. Carvalho, Jan Chomicki, Vincent Conitzer, Michael T. Cox, Virginia Dignum, Zachary Dodds, Mark Dredze, David Furcy, Evgeniy Gabrilovich, Mehmet H. Göker, Hans W. Guesgen, Haym Hirsh, Dietmar Jannach, Ulrich Junker, Wolfgang Ketter, Alfred Kobsa, Sven Koenig, Tessa A. Lau, Lundy Lewis, Eric T. Matson, Ted Metzler, Rada Mihalcea, Bamshad Mobasher, Joelle Pineau, Pascal Poupart, Anita Raja, Wheeler Ruml, Norman M. Sadeh, Guy Shani, Daniel G. Shapiro, Sarabjot Singh Anand, Matthew E. Taylor, Kiri Wagstaff, Trey Smith, William E. Walsh, Ron Zhou: AAAI 2008 Workshop Reports. AI Magazine 30(1): 108-118 (2009)
- 2008
- [j20]Haym Hirsh: Data Mining Research: Current Status and Future Opportunities. Statistical Analysis and Data Mining 1(2): 104-107 (2008)
- 2007
- [j19]Sarah Zelikovitz, William W. Cohen, Haym Hirsh: Extending WHIRL with background knowledge for improved text classification. Inf. Retr. 10(1): 35-67 (2007)
- 2006
- [c45]Alexander L. Strehl, Chris Mesterharm, Michael L. Littman, Haym Hirsh: Experience-efficient learning in associative bandit problems. ICML 2006: 889-896
- 2005
- [j18]Matthew Stone, Haym Hirsh: Artificial Intelligence: The Next Twenty-Five Years. AI Magazine 26(4): 85-97 (2005)
- [c44]Alexander Borgida, Thomas J. Walsh, Haym Hirsh: Towards Measuring Similarity in Description Logics. Description Logics 2005
- [c43]Sarah Zelikovitz, Haym Hirsh: Improving Text Classification Using EM with Background Text. FLAIRS Conference 2005: 499-505
- 2004
- [j17]Haym Hirsh, Nina Mishra, Leonard Pitt: Version spaces and the consistency problem. Artif. Intell. 156(2): 115-138 (2004)
- 2003
- [j16]Sofus A. Macskassy, Haym Hirsh, Arunava Banerjee, Aynur A. Dayanik: Converting numerical classification into text classification. Artif. Intell. 143(1): 51-77 (2003)
- [c42]
- [c41]Sarah Zelikovitz, Haym Hirsh: Integrating Background Knowledge Into Text Classification. IJCAI 2003: 1448-1449
- 2002
- [j15]Steve A. Chien, Haym Hirsh: Editorial Introduction: The Fourteenth Innovative Applications of Artificial Intelligence Conference (IAAI-2001). AI Magazine 23(2): 9-10 (2002)
- [c40]Sarah Zelikovitz, Haym Hirsh: Integrating Background Knowledge into Nearest-Neighbor Text Classification. ECCBR 2002: 1-5
- 2001
- [j14]Robert S. Engelmore, Haym Hirsh: Editorial Introduction to this Special Issue of AI Magazine: The Twelfth Innovative Applications of Artificial Intelligence Conference (IAAI-2000). AI Magazine 22(2): 13-14 (2001)
- [j13]Chumki Basu, Haym Hirsh, William W. Cohen, Craig G. Nevill-Manning: Technical Paper Recommendation: A Study in Combining Multiple Information Sources. J. Artif. Intell. Res. (JAIR) 14: 231-252 (2001)
- [c39]Sarah Zelikovitz, Haym Hirsh: Using LSI for Text Classification in the Presence of Background Text. CIKM 2001: 113-118
- [c38]Sofus A. Macskassy, Haym Hirsh, Arunava Banerjee, Aynur A. Dayanik: Using Text Classifiers for Numerical Classification. IJCAI 2001: 885-890
- [c37]Sofus A. Macskassy, Haym Hirsh, Foster J. Provost, Ramesh Sankaranarayanan, Vasant Dhar: Intelligent Information Triage. SIGIR 2001: 318-326
- [e2]Haym Hirsh, Steve A. Chien (Eds.): Proceedings of the Thirteenth Innovative Applications of Artificial Intelligence Conference, August 7-9, 2001, Seattle, Washington, USA. AAAI 2001, ISBN 1-57735-134-7
- 2000
- [j12]Haym Hirsh, Chumki Basu, Brian D. Davison: Enabling technologies: learning to personalize. Commun. ACM 43(8): 102-106 (2000)
- [j11]Marti A. Hearst, Haym Hirsh: AI's Greatest Trends and Controversies. IEEE Intelligent Systems 15(1): 8-17 (2000)
- [c36]
- [c35]Khaled Rasheed, Haym Hirsh: Informed operators: Speeding up genetic-algorithm-based design optimization using reduced models. GECCO 2000: 628-635
- [c34]Sarah Zelikovitz, Haym Hirsh: Improving Short-Text Classification using Unlabeled Data for Classification Problems. ICML 2000: 1191-1198
1990 – 1999
- 1999
- [j10]Khaled Rasheed, Haym Hirsh: Learning to be selective in genetic-algorithm-based design optimization. AI EDAM 13(3): 157-169 (1999)
- [c33]
- 1998
- [j9]Mark Schwabacher, Thomas Ellman, Haym Hirsh: Learning to set up numerical optimizations of engineering designs. AI EDAM 12(2): 173-192 (1998)
- [j8]Haym Hirsh: Trends & Controversies: Interactive Fiction. IEEE Intelligent Systems 13(6): 12-21 (1998)
- [j7]Ronen Feldman, Ido Dagan, Haym Hirsh: Mining Text Using Keyword Distributions. J. Intell. Inf. Syst. 10(3): 281-300 (1998)
- [c32]Chumki Basu, Haym Hirsh, William W. Cohen: Recommendation as Classification: Using Social and Content-Based Information in Recommendation. AAAI/IAAI 1998: 714-720
- [c31]
- [c30]
- [c29]William W. Cohen, Haym Hirsh: Joins that Generalize: Text Classification Using WHIRL. KDD 1998: 169-173
- [c28]Sofus A. Macskassy, Arunava Banerjee, Brian D. Davison, Haym Hirsh: Human Performance on Clustering Web Pages: A Preliminary Study. KDD 1998: 264-268
- [c27]
- [c26]Ronen Feldman, Moshe Fresko, Haym Hirsh, Yonatan Aumann, Orly Liphstat, Yonatan Schler, Martin Rajman: Knowledge Management: A Text Mining Approach. PAKM 1998
- 1997
- [j6]Khaled Rasheed, Haym Hirsh, Andrew Gelsey: A genetic algorithm for continuous design space search. AI in Engineering 11(3): 295-305 (1997)
- [j5]Ronen Feldman, Haym Hirsh: Exploiting Background Information in Knowledge Discovery from Text. J. Intell. Inf. Syst. 9(1): 83-97 (1997)
- [c25]
- [c24]Haym Hirsh, Nina Mishra, Leonard Pitt: Version Spaces without Boundary Sets. AAAI/IAAI 1997: 491-496
- [c23]
- [c22]
- [c21]
- [c20]Khaled Rasheed, Haym Hirsh: Using Case Based Learning to Improve Genetic Algorithm Based Design Optimization. ICGA 1997: 513-520
- 1996
- [j4]Mark Schwabacher, Thomas Ellman, Haym Hirsh: Inductive learning for engineering design optimization. AI EDAM 10(2): 179-180 (1996)
- [c19]Daniel Kudenko, Haym Hirsh: Representing Sequences in Description Logics Using Suffix Trees. Description Logics 1996: 141-145
- [c18]Ronen Feldman, Haym Hirsh: Mining Associations in Text in the Presence of Background Knowledge. KDD 1996: 343-346
- [c17]Kwong Bor Ng, David Loewenstern, Chumki Basu, Haym Hirsh, Paul B. Kantor: Data Fusion of Machine-Learning Methods for the TREC5 Routing Task (and other work). TREC 1996
- 1995
- [c16]William W. Cohen, Haym Hirsh: Corrigendum for ``Learnability of Description Logics''. COLT 1995: 463
- 1994
- [j3]Haym Hirsh, Michiel O. Noordewier: Using Background Knowledge to Improve Inductive Learning: A Case Study in Molecular Biology. IEEE Expert 9(5): 3-6 (1994)
- [j2]
- [j1]William W. Cohen, Haym Hirsh: The Learnability of Description Logics with Equality Constraints. Machine Learning 17(2-3): 169-199 (1994)
- [c15]Haym Hirsh, Nathalie Japkowicz: Bootstrapping Training-Data Representations for Inductive Learning: A Case Study in Molecular Biology. AAAI 1994: 639-644
- [c14]William W. Cohen, Haym Hirsh: Learning the Classic Description Logic: Theoretical and Experimental Results. KR 1994: 121-133
- [e1]William W. Cohen, Haym Hirsh (Eds.): Machine Learning, Proceedings of the Eleventh International Conference, Rutgers University, New Brunswick, NJ, USA, July 10-13, 1994. Morgan Kaufmann 1994, ISBN 1-55860-335-2
- 1993
- [c13]Steven W. Norton, Haym Hirsh: Learning DNF Via Probabilistic Evidence Combination. ICML 1993: 220-227
- 1992
- [c12]
- [c11]Steven W. Norton, Haym Hirsh: Classifier Learning from Noisy Data as Probabilistic Evidence Combination. AAAI 1992: 141-146
- [c10]William W. Cohen, Alexander Borgida, Haym Hirsh: Computing Least Common Subsumers in Description Logics. AAAI 1992: 754-760
- [c9]
- 1991
- [c8]
- 1990
- [c7]
- [c6]
1980 – 1989
- 1989
- [c5]
- [c4]Melissa P. Chase, Monte Zweben, Richard L. Piazza, John D. Burger, Paul P. Maglio, Haym Hirsh: Approximating Learned Search Control Knowledge. ML 1989: 218-220
- [c3]Scott H. Clearwater, Tze-Pin Chen, Haym Hirsh, Bruce G. Buchanan: Incremental Batch Learning. ML 1989: 366-370
- 1988
- [c2]
- 1987
- [c1]Haym Hirsh: Explanation-based Generalization in a Logic- Programming Environment. IJCAI 1987: 221-227
Coauthor Index
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last updated on 2013-05-09 22:07 CEST by the dblp team