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Shaul Markovitch
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Publications
- 2020
- [c49]Guy Kushilevitz, Shaul Markovitch, Yoav Goldberg:
A Two-Stage Masked LM Method for Term Set Expansion. ACL 2020: 6829-6835 - [i15]Guy Kushilevitz, Shaul Markovitch, Yoav Goldberg:
A Two-Stage Masked LM Method for Term Set Expansion. CoRR abs/2005.01063 (2020) - 2017
- [c46]Yotam Eshel, Noam Cohen, Kira Radinsky, Shaul Markovitch, Ikuya Yamada, Omer Levy:
Named Entity Disambiguation for Noisy Text. CoNLL 2017: 58-68 - [i10]Yotam Eshel, Noam Cohen, Kira Radinsky, Shaul Markovitch, Ikuya Yamada, Omer Levy:
Named Entity Disambiguation for Noisy Text. CoRR abs/1706.09147 (2017) - 2014
- [c44]Assaf Glazer, Omer Weissbrod, Michael Lindenbaum, Shaul Markovitch:
Approximating Hierarchical MV-sets for Hierarchical Clustering. NIPS 2014: 999-1007 - [i8]Evgeniy Gabrilovich, Shaul Markovitch:
Wikipedia-based Semantic Interpretation for Natural Language Processing. CoRR abs/1401.5697 (2014) - [i6]Kira Radinsky, Sagie Davidovich, Shaul Markovitch:
Learning to Predict from Textual Data. CoRR abs/1402.0574 (2014) - 2013
- [c43]Assaf Glazer, Michael Lindenbaum, Shaul Markovitch:
q-OCSVM: A q-Quantile Estimator for High-Dimensional Distributions. NIPS 2013: 503-511 - 2012
- [j27]Kira Radinsky, Sagie Davidovich, Shaul Markovitch:
Learning to Predict from Textual Data. J. Artif. Intell. Res. 45: 641-684 (2012) - [c42]Ariel Raviv, Shaul Markovitch:
Concept-Based Approach to Word-Sense Disambiguation. AAAI 2012: 807-813 - [c41]Omer Levy, Shaul Markovitch:
Teaching Machines to Learn by Metaphors. AAAI 2012: 991-997 - [c40]Assaf Glazer, Michael Lindenbaum, Shaul Markovitch:
One-Class Background Model. ACCV Workshops (1) 2012: 301-307 - [c39]Tamar Avraham, Ilya Gurvich, Michael Lindenbaum, Shaul Markovitch:
Learning Implicit Transfer for Person Re-identification. ECCV Workshops (1) 2012: 381-390 - [c38]Assaf Glazer, Michael Lindenbaum, Shaul Markovitch:
Feature shift detection. ICPR 2012: 1383-1386 - [c37]Assaf Glazer, Michael Lindenbaum, Shaul Markovitch:
Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data. NIPS 2012: 737-745 - [c36]Kira Radinsky, Sagie Davidovich, Shaul Markovitch:
Learning causality for news events prediction. WWW 2012: 909-918 - 2011
- [j25]Ofer Egozi, Shaul Markovitch, Evgeniy Gabrilovich:
Concept-Based Information Retrieval Using Explicit Semantic Analysis. ACM Trans. Inf. Syst. 29(2): 8:1-8:34 (2011) - [c33]Kira Radinsky, Eugene Agichtein, Evgeniy Gabrilovich, Shaul Markovitch:
A word at a time: computing word relatedness using temporal semantic analysis. WWW 2011: 337-346 - [i4]Lev Finkelstein, Shaul Markovitch, Ehud Rivlin:
Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Shared Resources. CoRR abs/1106.5269 (2011) - [i2]Dmitry Davidov, Shaul Markovitch:
Multiple-Goal Heuristic Search. CoRR abs/1109.6618 (2011) - 2009
- [j24]Evgeniy Gabrilovich, Shaul Markovitch:
Wikipedia-based Semantic Interpretation for Natural Language Processing. J. Artif. Intell. Res. 34: 443-498 (2009) - 2008
- [c31]Ofer Egozi, Evgeniy Gabrilovich, Shaul Markovitch:
Concept-Based Feature Generation and Selection for Information Retrieval. AAAI 2008: 1132-1137 - [c30]Kira Radinsky, Sagie Davidovich, Shaul Markovitch:
Predicting theNews of Tomorrow Using Patterns in Web Search Queries. Web Intelligence 2008: 363-367 - 2007
- [j21]Evgeniy Gabrilovich, Shaul Markovitch:
Harnessing the Expertise of 70, 000 Human Editors: Knowledge-Based Feature Generation for Text Categorization. J. Mach. Learn. Res. 8: 2297-2345 (2007) - [c28]Evgeniy Gabrilovich, Shaul Markovitch:
Computing Semantic Relatedness Using Wikipedia-based Explicit Semantic Analysis. IJCAI 2007: 1606-1611 - 2006
- [j20]Dmitry Davidov, Shaul Markovitch:
Multiple-Goal Heuristic Search. J. Artif. Intell. Res. 26: 417-451 (2006) - [c25]Nela Gurevich, Shaul Markovitch, Ehud Rivlin:
Active Learning with Near Misses. AAAI 2006: 362-367 - [c24]Evgeniy Gabrilovich, Shaul Markovitch:
Overcoming the Brittleness Bottleneck using Wikipedia: Enhancing Text Categorization with Encyclopedic Knowledge. AAAI 2006: 1301-1306 - 2005
- [c21]Evgeniy Gabrilovich, Shaul Markovitch:
Feature Generation for Text Categorization Using World Knowledge. IJCAI 2005: 1048-1053 - 2004
- [j17]Michael Lindenbaum, Shaul Markovitch, Dmitry Rusakov:
Selective Sampling for Nearest Neighbor Classifiers. Mach. Learn. 54(2): 125-152 (2004) - [c19]Evgeniy Gabrilovich, Shaul Markovitch:
Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5. ICML 2004 - [c18]Dmitry Davidov, Evgeniy Gabrilovich, Shaul Markovitch:
Parameterized generation of labeled datasets for text categorization based on a hierarchical directory. SIGIR 2004: 250-257 - 2003
- [j15]Lev Finkelstein, Shaul Markovitch, Ehud Rivlin:
Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Shared Resources. J. Artif. Intell. Res. 19: 73-138 (2003) - 2002
- [c17]Dmitry Davidov, Shaul Markovitch:
Multiple-Goal Search Algorithms and their Application to Web Crawling. AAAI/IAAI 2002: 713-718 - [c16]Lev Finkelstein, Shaul Markovitch, Ehud Rivlin:
Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Independent Processes. AAAI/IAAI 2002: 719-724 - 2001
- [j12]Lev Finkelstein, Shaul Markovitch:
Optimal schedules for monitoring anytime algorithms. Artif. Intell. 126(1-2): 63-108 (2001) - 1999
- [j11]David Carmel, Shaul Markovitch:
Exploration Strategies for Model-based Learning in Multi-agent Systems: Exploration Strategies. Auton. Agents Multi Agent Syst. 2(2): 141-172 (1999) - [c15]Michael Lindenbaum, Shaul Markovitch, Dmitry Rusakov:
Selective Sampling for Nearest Neighbor Classifiers. AAAI/IAAI 1999: 366-371 - 1998
- [j10]David Carmel, Shaul Markovitch:
Pruning Algorithms for Multi-Model Adversary Search. Artif. Intell. 99(2): 325-355 (1998) - [j9]Lev Finkelstein, Shaul Markovitch:
Learning to Play Chess Selectively by Acquiring Move Patterns. J. Int. Comput. Games Assoc. 21(2): 100-119 (1998) - [j8]David Carmel, Shaul Markovitch:
Pruning Algorithms for Multi-model Adversary Search. J. Int. Comput. Games Assoc. 21(3): 193 (1998) - [j7]Lev Finkelstein, Shaul Markovitch:
A Selective Macro-learning Algorithm and its Application to the NxN Sliding-Tile Puzzle. J. Artif. Intell. Res. 8: 223-263 (1998) - [j5]David Carmel, Shaul Markovitch:
Model-based learning of interaction strategies in multi-agent systems. J. Exp. Theor. Artif. Intell. 10(3): 309-332 (1998) - [c13]David Carmel, Shaul Markovitch:
How to Explore your Opponent's Strategy (almost) Optimally. ICMAS 1998: 64-71 - [i1]Lev Finkelstein, Shaul Markovitch:
A Selective Macro-learning Algorithm and its Application to the NxN Sliding-Tile Puzzle. CoRR cs.AI/9806102 (1998) - 1997
- [c12]David Carmel, Shaul Markovitch:
Exploration and Adaptation in Multiagent Systems: A Model-based Approach. IJCAI (1) 1997: 606-611 - 1996
- [c11]David Carmel, Shaul Markovitch:
Learning Models of Intelligent Agents. AAAI/IAAI, Vol. 1 1996: 62-67 - [c10]David Carmel, Shaul Markovitch:
Incorporating Opponent Models into Adversary Search. AAAI/IAAI, Vol. 1 1996: 120-125 - 1995
- [j3]Ido Dagan, Shaul Marcus, Shaul Markovitch:
Contextual word similarity and estimation from sparse data. Comput. Speech Lang. 9(2): 123-152 (1995) - [c9]David Carmel, Shaul Markovitch:
Opponent Modeling in Multi-Agent Systems. Adaption and Learning in Multi-Agent Systems 1995: 40-52 - 1993
- [c8]Ido Dagan, Shaul Marcus, Shaul Markovitch:
Contextual Word Similarity and Estimation from Sparse Data. ACL 1993: 164-171
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