Haym Hirsh - RankMe

83 papers A* 21A 3B 1C 1Misc 1Journal 29Unranked 25

Year	Rank	Type	Title / Venue / Authors
2020	J	`jnl`	Accelerating evidence-informed decision-making for the Sustainable Development Goals using machine learning. Nat. Mach. Intell. Jaron Porciello, Maryia Ivanina, Maidul Islam, Stefan Einarson, Haym Hirsh
2016	B	`conf`	Interactive Consensus Agreement Games for Labeling Images. HCOMP Paul Upchurch, Daniel Sedra, Andrew Mullen, Haym Hirsh, Kavita Bala
2015	J	`jnl`	A U.S. Research Roadmap for Human Computation. CoRR Pietro Michelucci, Lea Shanley, Janis Dickinson, Haym Hirsh
2014	J	`jnl`	Antisocial computing: exploring design risks in social computing systems. Interactions David W. McDonald, David H. Ackley, Randal E. Bryant, Melissa Gedney, Haym Hirsh, Lea Shanley
2014	J	`jnl`	Approximating the crowd. Data Min. Knowl. Discov. Seyda Ertekin, Cynthia Rudin, Haym Hirsh
2013	—	`ch.`	Human Computation in the Wild. Handbook of Human Computation Haym Hirsh
2013	J	`jnl`	Reports on the 2012 AAAI Fall Symposium Series. AI Mag. 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
2012	—	`conf`	Diamonds From the Rough: Improving Drawing, Painting, and Singing via Crowdsourcing. HCOMP@AAAI Yotam I. Gingold, Etienne Vouga, Eitan Grinspun, Haym Hirsh
2012	—	`conf`	Discovery Informatics: AI Opportunities in Scientific Discovery. AAAI Fall Symposium: Discovery Informatics Yolanda Gil, Haym Hirsh
2012	J	`jnl`	Learning to Predict the Wisdom of Crowds CoRR Seyda Ertekin, Haym Hirsh, Cynthia Rudin
2012	—	`conf`	Preface. AAAI Fall Symposium: Discovery Informatics Will Bridewell, Yolanda Gil, Haym Hirsh, Kerstin Kleese van Dam, Karsten Steinhaeuser
2012	—	`conf`	Selective Sampling of Labelers for Approximating the Crowd. AAAI Fall Symposium: Machine Aggregation of Human Judgment Seyda Ertekin, Haym Hirsh, Cynthia Rudin
2011	J	`jnl`	Technical Paper Recommendation: A Study in Combining Multiple Information Sources CoRR Chumki Basu, William W. Cohen, Haym Hirsh, Craig G. Nevill-Manning
2009	J	`jnl`	AAAI 2008 Workshop Reports. AI Mag. 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
2008	J	`jnl`	Data Mining Research: Current Status and Future Opportunities. Stat. Anal. Data Min. Haym Hirsh
2007	J	`jnl`	Extending WHIRL with background knowledge for improved text classification. Inf. Retr. Sarah Zelikovitz, William W. Cohen, Haym Hirsh
2006	A*	`conf`	Experience-efficient learning in associative bandit problems. ICML Alexander L. Strehl, Chris Mesterharm, Michael L. Littman, Haym Hirsh
2005	J	`jnl`	Artificial Intelligence: The Next Twenty-Five Years. AI Mag. Matthew Stone, Haym Hirsh
2005	Misc	`conf`	Improving Text Classification Using EM with Background Text. FLAIRS Sarah Zelikovitz, Haym Hirsh
2005	—	`conf`	Towards Measuring Similarity in Description Logics. Description Logics Alexander Borgida, Thomas J. Walsh, Haym Hirsh
2004	J	`jnl`	Version spaces and the consistency problem. Artif. Intell. Haym Hirsh, Nina Mishra, Leonard Pitt
2003	A	`conf`	Adding numbers to text classification. CIKM Sofus A. Macskassy, Haym Hirsh
2003	J	`jnl`	Converting numerical classification into text classification. Artif. Intell. Sofus A. Macskassy, Haym Hirsh, Arunava Banerjee, Aynur A. Dayanik
2003	A*	`conf`	Integrating Background Knowledge Into Text Classification. IJCAI Sarah Zelikovitz, Haym Hirsh
2002	J	`jnl`	Editorial Introduction: The Fourteenth Innovative Applications of Artificial Intelligence Conference (IAAI-2001). AI Mag. Steve A. Chien, Haym Hirsh
2002	—	`conf`	Integrating Background Knowledge into Nearest-Neighbor Text Classification. ECCBR Sarah Zelikovitz, Haym Hirsh
2001	J	`jnl`	Editorial Introduction to this Special Issue of AI Magazine: The Twelfth Innovative Applications of Artificial Intelligence Conference (IAAI-2000). AI Mag. Robert S. Engelmore, Haym Hirsh
2001	A*	`conf`	Intelligent Information Triage. SIGIR Sofus A. Macskassy, Haym Hirsh, Foster J. Provost, Ramesh Sankaranarayanan, Vasant Dhar
2001	C	`ed.`	Proceedings of the Thirteenth Innovative Applications of Artificial Intelligence Conference, August 7-9, 2001, Seattle, Washington, USA IAAI Haym Hirsh, Steve A. Chien
2001	J	`jnl`	Technical Paper Recommendation: A Study in Combining Multiple Information Sources. J. Artif. Intell. Res. Chumki Basu, Haym Hirsh, William W. Cohen, Craig G. Nevill-Manning
2001	A	`conf`	Using LSI for Text Classification in the Presence of Background Text. CIKM Sarah Zelikovitz, Haym Hirsh
2001	A*	`conf`	Using Text Classifiers for Numerical Classification. IJCAI Sofus A. Macskassy, Haym Hirsh, Arunava Banerjee, Aynur A. Dayanik
2000	—	`conf`	A Quantitative Study of Small Disjuncts. AAAI/IAAI Gary M. Weiss, Haym Hirsh
2000	J	`jnl`	AI's Greatest Trends and Controversies. IEEE Intell. Syst. Marti A. Hearst, Haym Hirsh
2000	J	`jnl`	Enabling technologies: learning to personalize. Commun. ACM Haym Hirsh, Chumki Basu, Brian D. Davison
2000	A*	`conf`	Improving Short-Text Classification using Unlabeled Data for Classification Problems. ICML Sarah Zelikovitz, Haym Hirsh
2000	A	`conf`	Informed operators: Speeding up genetic-algorithm-based design optimization using reduced models. GECCO Khaled Rasheed, Haym Hirsh
1999	—	`conf`	Feature-Based Learners for Description Logics. Description Logics Daniel Kudenko, Haym Hirsh
1999	J	`jnl`	Learning to be selective in genetic-algorithm-based design optimization. Artif. Intell. Eng. Des. Anal. Manuf. Khaled Rasheed, Haym Hirsh
1999	J	`jnl`	Room service, AI-style. IEEE Intell. Syst. Haym Hirsh, Michael H. Coen, Michael C. Mozer, Richard Hasha, James L. Flanagan
1998	—	`conf`	Feature Generation for Sequence Categorization. AAAI/IAAI Daniel Kudenko, Haym Hirsh
1998	A*	`conf`	Human Performance on Clustering Web Pages: A Preliminary Study. KDD Sofus A. Macskassy, Arunava Banerjee, Brian D. Davison, Haym Hirsh
1998	A*	`conf`	Joins that Generalize: Text Classification Using WHIRL. KDD William W. Cohen, Haym Hirsh
1998	—	`conf`	Knowledge Management: A Text Mining Approach. PAKM Ronen Feldman, Moshe Fresko, Haym Hirsh, Yonatan Aumann, Orly Liphstat, Yonatan Schler, Martin Rajman
1998	A*	`conf`	Learning to Predict Rare Events in Event Sequences. KDD Gary M. Weiss, Haym Hirsh
1998	J	`jnl`	Learning to set up numerical optimizations of engineering designs. Artif. Intell. Eng. Des. Anal. Manuf. Mark Schwabacher, Thomas Ellman, Haym Hirsh
1998	J	`jnl`	Mining Text Using Keyword Distributions. J. Intell. Inf. Syst. Ronen Feldman, Ido Dagan, Haym Hirsh
1998	—	`conf`	Recommendation as Classification: Using Social and Content-Based Information in Recommendation. AAAI/IAAI Chumki Basu, Haym Hirsh, William W. Cohen
1998	A*	`conf`	The Problem with Noise and Small Disjuncts. ICML Gary M. Weiss, Haym Hirsh
1998	J	`jnl`	Trends & Controversies: Interactive Fiction. IEEE Intell. Syst. Haym Hirsh
1997	J	`jnl`	A genetic algorithm for continuous design space search. Artif. Intell. Eng. Khaled Rasheed, Haym Hirsh, Andrew Gelsey
1997	—	`conf`	An Adaptive UNIX Command-Line Assistant. Agents Haym Hirsh, Brian D. Davison
1997	—	`conf`	Experiments in UNIX Command Prediction. AAAI/IAAI Brian D. Davison, Haym Hirsh
1997	J	`jnl`	Exploiting Background Information in Knowledge Discovery from Text. J. Intell. Inf. Syst. Ronen Feldman, Haym Hirsh
1997	—	`conf`	Representing Sequences in Description Logics. AAAI/IAAI Haym Hirsh, Daniel Kudenko
1997	—	`conf`	Toward an Adaptive Command Line Interface. HCI (2) Brian D. Davison, Haym Hirsh
1997	—	`conf`	Using Case Based Learning to Improve Genetic Algorithm Based Design Optimization. ICGA Khaled Rasheed, Haym Hirsh
1997	—	`conf`	Version Spaces without Boundary Sets. AAAI/IAAI Haym Hirsh, Nina Mishra, Leonard Pitt
1996	—	`conf`	Data Fusion of Machine-Learning Methods for the TREC5 Routing Task (and other work). TREC Kwong Bor Ng, David Loewenstern, Chumki Basu, Haym Hirsh, Paul B. Kantor
1996	J	`jnl`	Inductive learning for engineering design optimization. Artif. Intell. Eng. Des. Anal. Manuf. Mark Schwabacher, Thomas Ellman, Haym Hirsh
1996	A*	`conf`	Mining Associations in Text in the Presence of Background Knowledge. KDD Ronen Feldman, Haym Hirsh
1996	—	`conf`	Representing Sequences in Description Logics Using Suffix Trees. Description Logics Daniel Kudenko, Haym Hirsh
1995	A*	`conf`	Corrigendum for "Learnability of Description Logics". COLT William W. Cohen, Haym Hirsh
1994	A*	`conf`	Bootstrapping Training-Data Representations for Inductive Learning: A Case Study in Molecular Biology. AAAI Haym Hirsh, Nathalie Japkowicz
1994	J	`jnl`	Generalizing Version Spaces. Mach. Learn. Haym Hirsh
1994	A*	`conf`	Learning the Classic Description Logic: Theoretical and Experimental Results. KR William W. Cohen, Haym Hirsh
1994	A*	`ed.`	Machine Learning, Proceedings of the Eleventh International Conference, Rutgers University, New Brunswick, NJ, USA, July 10-13, 1994 ICML William W. Cohen, Haym Hirsh
1994	J	`jnl`	The Learnability of Description Logics with Equality Constraints. Mach. Learn. William W. Cohen, Haym Hirsh
1994	J	`jnl`	Using Background Knowledge to Improve Inductive Learning: A Case Study in Molecular Biology. IEEE Expert Haym Hirsh, Michiel O. Noordewier
1993	A*	`conf`	Learning DNF Via Probabilistic Evidence Combination. ICML Steven W. Norton, Haym Hirsh
1992	A*	`conf`	Classifier Learning from Noisy Data as Probabilistic Evidence Combination. AAAI Steven W. Norton, Haym Hirsh
1992	A*	`conf`	Computing Least Common Subsumers in Description Logics. AAAI William W. Cohen, Alexander Borgida, Haym Hirsh
1992	A*	`conf`	Learnability of Description Logics. COLT William W. Cohen, Haym Hirsh
1992	A*	`conf`	Polynomial-Time Learning with Version Spaces. AAAI Haym Hirsh
1991	A*	`conf`	Theoretical Underpinnings of Version Spaces. IJCAI Haym Hirsh
1990	—	`conf`	Incremental Version-Space Merging. ML Haym Hirsh
1990	—	`conf`	Learning from Data with Bounded Inconsistency. ML Haym Hirsh
1989	—	`conf`	Approximating Learned Search Control Knowledge. ML Melissa P. Chase, Monte Zweben, Richard L. Piazza, John D. Burger, Paul P. Maglio, Haym Hirsh
1989	—	`conf`	Combining Empirical and Analytical Learning with Version Spaces. ML Haym Hirsh
1989	—	`conf`	Incremental Batch Learning. ML Scott H. Clearwater, Tze-Pin Chen, Haym Hirsh, Bruce G. Buchanan
1989	—	`—`	Incremental version-space merging : a general framework for concept learning. Haym Hirsh
1988	—	`conf`	Reasoning about Operationality for Explanation-Based Learning. ML Haym Hirsh
1987	A*	`conf`	Explanation-based Generalization in a Logic-Programming Environment. IJCAI Haym Hirsh