| 2007 |
|---|
| 64 | EE | Sarah Zelikovitz,
William W. Cohen,
Haym Hirsh:
Extending WHIRL with background knowledge for improved text classification.
Inf. Retr. 10(1): 35-67 (2007) |
| 2006 |
|---|
| 63 | EE | Alexander L. Strehl,
Chris Mesterharm,
Michael L. Littman,
Haym Hirsh:
Experience-efficient learning in associative bandit problems.
ICML 2006: 889-896 |
| 2005 |
|---|
| 62 | EE | Alexander Borgida,
Thomas Walsh,
Haym Hirsh:
Towards Measuring Similarity in Description Logics.
Description Logics 2005 |
| 61 | | Sarah Zelikovitz,
Haym Hirsh:
Improving Text Classification Using EM with Background Text.
FLAIRS Conference 2005: 499-505 |
| 60 | | Matthew Stone,
Haym Hirsh:
Artificial Intelligence: The Next Twenty-Five Years.
AI Magazine 26(4): 85-97 (2005) |
| 2004 |
|---|
| 59 | EE | Haym Hirsh,
Nina Mishra,
Leonard Pitt:
Version spaces and the consistency problem.
Artif. Intell. 156(2): 115-138 (2004) |
| 2003 |
|---|
| 58 | EE | Sofus A. Macskassy,
Haym Hirsh:
Adding numbers to text classification.
CIKM 2003: 240-246 |
| 57 | | Sarah Zelikovitz,
Haym Hirsh:
Integrating Background Knowledge Into Text Classification.
IJCAI 2003: 1448-1449 |
| 56 | EE | Sofus A. Macskassy,
Haym Hirsh,
Arunava Banerjee,
Aynur A. Dayanik:
Converting numerical classification into text classification.
Artif. Intell. 143(1): 51-77 (2003) |
| 2002 |
|---|
| 55 | EE | Sarah Zelikovitz,
Haym Hirsh:
Integrating Background Knowledge into Nearest-Neighbor Text Classification.
ECCBR 2002: 1-5 |
| 54 | | Steve A. Chien,
Haym Hirsh:
Editorial Introduction: The Fourteenth Innovative Applications of Artificial Intelligence Conference (IAAI-2001).
AI Magazine 23(2): 9-10 (2002) |
| 2001 |
|---|
| 53 | | Haym Hirsh,
Steve A. Chien:
Proceedings of the Thirteenth Innovative Applications of Artificial Intelligence Conference, August 7-9, 2001, Seattle, Washington, USA
AAAI 2001 |
| 52 | | Sarah Zelikovitz,
Haym Hirsh:
Using LSI for Text Classification in the Presence of Background Text.
CIKM 2001: 113-118 |
| 51 | | Sofus A. Macskassy,
Haym Hirsh,
Arunava Banerjee,
Aynur A. Dayanik:
Using Text Classifiers for Numerical Classification.
IJCAI 2001: 885-890 |
| 50 | | Sofus A. Macskassy,
Haym Hirsh,
Foster J. Provost,
Ramesh Sankaranarayanan,
Vasant Dhar:
Intelligent Information Triage.
SIGIR 2001: 318-326 |
| 49 | | 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) |
| 48 | EE | 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) |
| 2000 |
|---|
| 47 | | Gary M. Weiss,
Haym Hirsh:
A Quantitative Study of Small Disjuncts.
AAAI/IAAI 2000: 665-670 |
| 46 | | Khaled Rasheed,
Haym Hirsh:
Informed operators: Speeding up genetic-algorithm-based design optimization using reduced models.
GECCO 2000: 628-635 |
| 45 | | Sarah Zelikovitz,
Haym Hirsh:
Improving Short-Text Classification using Unlabeled Data for Classification Problems.
ICML 2000: 1191-1198 |
| 44 | EE | Haym Hirsh,
Chumki Basu,
Brian D. Davison:
Enabling technologies: learning to personalize.
Commun. ACM 43(8): 102-106 (2000) |
| 43 | EE | Marti A. Hearst,
Haym Hirsh:
AI's Greatest Trends and Controversies.
IEEE Intelligent Systems 15(1): 8-17 (2000) |
| 1999 |
|---|
| 42 | EE | Daniel Kudenko,
Haym Hirsh:
Feature-Based Learners for Description Logics.
Description Logics 1999 |
| 41 | EE | Khaled Rasheed,
Haym Hirsh:
Learning to be selective in genetic-algorithm-based design optimization.
AI EDAM 13(3): 157-169 (1999) |
| 1998 |
|---|
| 40 | | Chumki Basu,
Haym Hirsh,
William W. Cohen:
Recommendation as Classification: Using Social and Content-Based Information in Recommendation.
AAAI/IAAI 1998: 714-720 |
| 39 | | Daniel Kudenko,
Haym Hirsh:
Feature Generation for Sequence Categorization.
AAAI/IAAI 1998: 733-738 |
| 38 | | Gary M. Weiss,
Haym Hirsh:
The Problem with Noise and Small Disjuncts.
ICML 1998: 574- |
| 37 | | William W. Cohen,
Haym Hirsh:
Joins that Generalize: Text Classification Using WHIRL.
KDD 1998: 169-173 |
| 36 | | Sofus A. Macskassy,
Arunava Banerjee,
Brian D. Davison,
Haym Hirsh:
Human Performance on Clustering Web Pages: A Preliminary Study.
KDD 1998: 264-268 |
| 35 | | Gary M. Weiss,
Haym Hirsh:
Learning to Predict Rare Events in Event Sequences.
KDD 1998: 359-363 |
| 34 | EE | Ronen Feldman,
Moshe Fresko,
Haym Hirsh,
Yonatan Aumann,
Orly Liphstat,
Yonatan Schler,
Martin Rajman:
Knowledge Management: A Text Mining Approach.
PAKM 1998 |
| 33 | EE | Mark Schwabacher,
Thomas Ellman,
Haym Hirsh:
Learning to set up numerical optimizations of engineering designs.
AI EDAM 12(2): 173-192 (1998) |
| 32 | | Haym Hirsh:
Trends & Controversies: Interactive Fiction.
IEEE Intelligent Systems 13(6): 12-21 (1998) |
| 31 | | Ronen Feldman,
Ido Dagan,
Haym Hirsh:
Mining Text Using Keyword Distributions.
J. Intell. Inf. Syst. 10(3): 281-300 (1998) |
| 1997 |
|---|
| 30 | | Haym Hirsh,
Daniel Kudenko:
Representing Sequences in Description Logics.
AAAI/IAAI 1997: 384-389 |
| 29 | | Haym Hirsh,
Nina Mishra,
Leonard Pitt:
Version Spaces without Boundary Sets.
AAAI/IAAI 1997: 491-496 |
| 28 | | Brian D. Davison,
Haym Hirsh:
Experiments in UNIX Command Prediction.
AAAI/IAAI 1997: 827 |
| 27 | | Haym Hirsh,
Brian D. Davison:
An Adaptive UNIX Command-Line Assistant.
Agents 1997: 542-543 |
| 26 | | Brian D. Davison,
Haym Hirsh:
Toward an Adaptive Command Line Interface.
HCI (2) 1997: 505-508 |
| 25 | | Khaled Rasheed,
Haym Hirsh:
Using Case Based Learning to Improve Genetic Algorithm Based Design Optimization.
ICGA 1997: 513-520 |
| 24 | EE | Khaled Rasheed,
Haym Hirsh,
Andrew Gelsey:
A genetic algorithm for continuous design space search.
AI in Engineering 11(3): 295-305 (1997) |
| 23 | | Ronen Feldman,
Haym Hirsh:
Exploiting Background Information in Knowledge Discovery from Text.
J. Intell. Inf. Syst. 9(1): 83-97 (1997) |
| 1996 |
|---|
| 22 | | Daniel Kudenko,
Haym Hirsh:
Representing Sequences in Description Logics Using Suffix Trees.
Description Logics 1996: 141-145 |
| 21 | | Ronen Feldman,
Haym Hirsh:
Mining Associations in Text in the Presence of Background Knowledge.
KDD 1996: 343-346 |
| 20 | EE | 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 |
|---|
| 19 | | William W. Cohen,
Haym Hirsh:
Corrigendum for ``Learnability of Description Logics''.
COLT 1995: 463 |
| 1994 |
|---|
| 18 | | Haym Hirsh,
Nathalie Japkowicz:
Bootstrapping Training-Data Representations for Inductive Learning: A Case Study in Molecular Biology.
AAAI 1994: 639-644 |
| 17 | | William W. Cohen,
Haym Hirsh:
Learning the Classic Description Logic: Theoretical and Experimental Results.
KR 1994: 121-133 |
| 16 | EE | 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) |
| 15 | | Haym Hirsh:
Generalizing Version Spaces.
Machine Learning 17(1): 5-46 (1994) |
| 14 | | William W. Cohen,
Haym Hirsh:
The Learnability of Description Logics with Equality Constraints.
Machine Learning 17(2-3): 169-199 (1994) |
| 1993 |
|---|
| 13 | | Steven W. Norton,
Haym Hirsh:
Learning DNF Via Probabilistic Evidence Combination.
ICML 1993: 220-227 |
| 1992 |
|---|
| 12 | | Haym Hirsh:
Polynomial-Time Learning with Version Spaces.
AAAI 1992: 117-122 |
| 11 | | Steven W. Norton,
Haym Hirsh:
Classifier Learning from Noisy Data as Probabilistic Evidence Combination.
AAAI 1992: 141-146 |
| 10 | | William W. Cohen,
Alexander Borgida,
Haym Hirsh:
Computing Least Common Subsumers in Description Logics.
AAAI 1992: 754-760 |
| 9 | EE | William W. Cohen,
Haym Hirsh:
Learnability of Description Logics.
COLT 1992: 116-127 |
| 1991 |
|---|
| 8 | | Haym Hirsh:
Theoretical Underpinnings of Version Spaces.
IJCAI 1991: 665-670 |
| 1990 |
|---|
| 7 | | Haym Hirsh:
Learning from Data with Bounded Inconsistency.
ML 1990: 32-39 |
| 6 | | Haym Hirsh:
Incremental Version-Space Merging.
ML 1990: 330-338 |
| 1989 |
|---|
| 5 | | 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 |
| 4 | | Haym Hirsh:
Combining Empirical and Analytical Learning with Version Spaces.
ML 1989: 29-33 |
| 3 | | Scott H. Clearwater,
Tze-Pin Chen,
Haym Hirsh,
Bruce G. Buchanan:
Incremental Batch Learning.
ML 1989: 366-370 |
| 1988 |
|---|
| 2 | | Haym Hirsh:
Reasoning about Operationality for Explanation-Based Learning.
ML 1988: 214-220 |
| 1987 |
|---|
| 1 | | Haym Hirsh:
Explanation-based Generalization in a Logic- Programming Environment.
IJCAI 1987: 221-227 |
