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ORCIDHaym Hirsh
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- affiliation: Rutgers University, USA
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2020 – today
- 2020
[j26]Jaron Porciello
, Maryia Ivanina, Maidul Islam, Stefan Einarson, Haym Hirsh:
Accelerating evidence-informed decision-making for the Sustainable Development Goals using machine learning. Nat. Mach. Intell. 2(10): 559-565 (2020)
2010 – 2019
- 2016
- [c50]Paul Upchurch, Daniel Sedra, Andrew Mullen, Haym Hirsh, Kavita Bala:
Interactive Consensus Agreement Games for Labeling Images. HCOMP 2016: 239-248 - 2015
- [i3]Pietro Michelucci, Lea Shanley, Janis Dickinson, Haym Hirsh:
A U.S. Research Roadmap for Human Computation. CoRR abs/1505.07096 (2015) - 2014
- [j25]Seyda Ertekin, Cynthia Rudin, Haym Hirsh:
Approximating the crowd. Data Min. Knowl. Discov. 28(5-6): 1189-1221 (2014) - [j24]David W. McDonald, David H. Ackley, Randal E. Bryant, Melissa Gedney, Haym Hirsh, Lea Shanley:
Antisocial computing: exploring design risks in social computing systems. Interactions 21(6): 72-75 (2014) - 2013
- [j23]Rezarta Islamaj Dogan, Yolanda Gil, Haym Hirsh, Narayanan Chatapuram 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 Mag. 34(1): 93-100 (2013) - [r1]Haym Hirsh:
Human Computation in the Wild. Handbook of Human Computation 2013: 89-93 - 2012
- [c49]Will Bridewell, Yolanda Gil, Haym Hirsh, Kerstin Kleese van Dam, Karsten Steinhaeuser:
Preface. AAAI Fall Symposium: Discovery Informatics 2012 - [c48]Seyda Ertekin, Haym Hirsh, Cynthia Rudin:
Selective Sampling of Labelers for Approximating the Crowd. AAAI Fall Symposium: Machine Aggregation of Human Judgment 2012 - [c47]Yolanda Gil, Haym Hirsh:
Discovery Informatics: AI Opportunities in Scientific Discovery. AAAI Fall Symposium: Discovery Informatics 2012 - [c46]Yotam I. Gingold, Etienne Vouga, Eitan Grinspun, Haym Hirsh:
Diamonds From the Rough: Improving Drawing, Painting, and Singing via Crowdsourcing. HCOMP@AAAI 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
- [j22]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, Rong Zhou:
AAAI 2008 Workshop Reports. AI Mag. 30(1): 108-118 (2009) - 2008
- [j21]Haym Hirsh:
Data Mining Research: Current Status and Future Opportunities. Stat. Anal. Data Min. 1(2): 104-107 (2008) - 2007
- [j20]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
- [j19]Matthew Stone, Haym Hirsh:
Artificial Intelligence: The Next Twenty-Five Years. AI Mag. 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 2005: 499-505 - 2004
- [j18]Haym Hirsh, Nina Mishra, Leonard Pitt:
Version spaces and the consistency problem. Artif. Intell. 156(2): 115-138 (2004) - 2003
- [j17]Sofus A. Macskassy, Haym Hirsh, Arunava Banerjee, Aynur A. Dayanik:
Converting numerical classification into text classification. Artif. Intell. 143(1): 51-77 (2003) - [c42]Sofus A. Macskassy, Haym Hirsh:
Adding numbers to text classification. CIKM 2003: 240-246 - [c41]Sarah Zelikovitz, Haym Hirsh:
Integrating Background Knowledge Into Text Classification. IJCAI 2003: 1448-1449 - 2002
- [j16]Steve A. Chien, Haym Hirsh:
Editorial Introduction: The Fourteenth Innovative Applications of Artificial Intelligence Conference (IAAI-2001). AI Mag. 23(2): 9-10 (2002) - [c40]Sarah Zelikovitz, Haym Hirsh:
Integrating Background Knowledge into Nearest-Neighbor Text Classification. ECCBR 2002: 1-5 - 2001
- [j15]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 Mag. 22(2): 13-14 (2001) - [j14]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. 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:
Proceedings of the Thirteenth Innovative Applications of Artificial Intelligence Conference, August 7-9, 2001, Seattle, Washington, USA. AAAI 2001, ISBN 1-57735-134-7 [contents] - 2000
- [j13]Haym Hirsh, Chumki Basu, Brian D. Davison:
Enabling technologies: learning to personalize. Commun. ACM 43(8): 102-106 (2000) - [j12]Marti A. Hearst, Haym Hirsh:
AI's Greatest Trends and Controversies. IEEE Intell. Syst. 15(1): 8-17 (2000) - [c36]Gary M. Weiss, Haym Hirsh:
A Quantitative Study of Small Disjuncts. AAAI/IAAI 2000: 665-670 - [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
- [j11]Khaled Rasheed, Haym Hirsh:
Learning to be selective in genetic-algorithm-based design optimization. Artif. Intell. Eng. Des. Anal. Manuf. 13(3): 157-169 (1999) - [j10]Haym Hirsh, Michael H. Coen, Michael C. Mozer, Richard Hasha, James L. Flanagan:
Room service, AI-style. IEEE Intell. Syst. 14(2): 8-19 (1999) - [c33]Daniel Kudenko, Haym Hirsh:
Feature-Based Learners for Description Logics. Description Logics 1999 - 1998
- [j9]Mark Schwabacher, Thomas Ellman, Haym Hirsh:
Learning to set up numerical optimizations of engineering designs. Artif. Intell. Eng. Des. Anal. Manuf. 12(2): 173-192 (1998) - [j8]Haym Hirsh:
Trends & Controversies: Interactive Fiction. IEEE Intell. Syst. 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]Daniel Kudenko, Haym Hirsh:
Feature Generation for Sequence Categorization. AAAI/IAAI 1998: 733-738 - [c30]Gary M. Weiss, Haym Hirsh:
The Problem with Noise and Small Disjuncts. ICML 1998: 574- - [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]Gary M. Weiss, Haym Hirsh:
Learning to Predict Rare Events in Event Sequences. KDD 1998: 359-363 - [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. Artif. Intell. Eng. 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]Haym Hirsh, Daniel Kudenko:
Representing Sequences in Description Logics. AAAI/IAAI 1997: 384-389 - [c24]Haym Hirsh, Nina Mishra, Leonard Pitt:
Version Spaces without Boundary Sets. AAAI/IAAI 1997: 491-496 - [c23]Brian D. Davison, Haym Hirsh:
Experiments in UNIX Command Prediction. AAAI/IAAI 1997: 827 - [c22]Haym Hirsh, Brian D. Davison:
An Adaptive UNIX Command-Line Assistant. Agents 1997: 542-543 - [c21]Brian D. Davison, Haym Hirsh:
Toward an Adaptive Command Line Interface. HCI (2) 1997: 505-508 - [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. Artif. Intell. Eng. Des. Anal. Manuf. 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]Haym Hirsh:
Generalizing Version Spaces. Mach. Learn. 17(1): 5-46 (1994) - [j1]William W. Cohen, Haym Hirsh:
The Learnability of Description Logics with Equality Constraints. Mach. Learn. 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:
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 [contents] - [d1]Haym Hirsh:
Badges. UCI Machine Learning Repository, 1994
- 1993
- [c13]Steven W. Norton, Haym Hirsh:
Learning DNF Via Probabilistic Evidence Combination. ICML 1993: 220-227 - 1992
- [c12]Haym Hirsh:
Polynomial-Time Learning with Version Spaces. AAAI 1992: 117-122 - [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]William W. Cohen, Haym Hirsh:
Learnability of Description Logics. COLT 1992: 116-127 - 1991
- [c8]Haym Hirsh:
Theoretical Underpinnings of Version Spaces. IJCAI 1991: 665-670 - 1990
- [c7]Haym Hirsh:
Learning from Data with Bounded Inconsistency. ML 1990: 32-39 - [c6]Haym Hirsh:
Incremental Version-Space Merging. ML 1990: 330-338
1980 – 1989
- 1989
- [b1]Haym Hirsh:
Incremental version-space merging : a general framework for concept learning. Stanford University, USA, 1989 - [c5]Haym Hirsh:
Combining Empirical and Analytical Learning with Version Spaces. ML 1989: 29-33 - [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]Haym Hirsh:
Reasoning about Operationality for Explanation-Based Learning. ML 1988: 214-220 - 1987
- [c1]Haym Hirsh:
Explanation-based Generalization in a Logic-Programming Environment. IJCAI 1987: 221-227
Coauthor Index
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