Shaul Markovitch

	2009
51		Evgeniy Gabrilovich, Shaul Markovitch: Wikipedia-based Semantic Interpretation for Natural Language Processing. J. Artif. Intell. Res. (JAIR) 34: 443-498 (2009)
	2008
50		Ofer Egozi, Evgeniy Gabrilovich, Shaul Markovitch: Concept-Based Feature Generation and Selection for Information Retrieval. AAAI 2008: 1132-1137
49		Kira Radinsky, Sagie Davidovich, Shaul Markovitch: Predicting theNews of Tomorrow Using Patterns in Web Search Queries. Web Intelligence 2008: 363-367
48		Saher Esmeir, Shaul Markovitch: Anytime Induction of Low-cost, Low-error Classifiers: a Sampling-based Approach. J. Artif. Intell. Res. (JAIR) 33: 1-31 (2008)
	2007
47		Evgeniy Gabrilovich, Shaul Markovitch: Computing Semantic Relatedness Using Wikipedia-based Explicit Semantic Analysis. IJCAI 2007: 1606-1611
46		Saher Esmeir, Shaul Markovitch: Occam's Razor Just Got Sharper. IJCAI 2007: 768-773
45		Saher Esmeir, Shaul Markovitch: Anytime Induction of Cost-sensitive Trees. NIPS 2007
	2006
44		Nela Gurevich, Shaul Markovitch, Ehud Rivlin: Active Learning with Near Misses. AAAI 2006
43		Saher Esmeir, Shaul Markovitch: Anytime Induction of Decision Trees: An Iterative Improvement Approach. AAAI 2006
42		Evgeniy Gabrilovich, Shaul Markovitch: Overcoming the Brittleness Bottleneck using Wikipedia: Enhancing Text Categorization with Encyclopedic Knowledge. AAAI 2006
41		Saher Esmeir, Shaul Markovitch: When a Decision Tree Learner Has Plenty of Time. AAAI 2006
40		Dmitry Davidov, Shaul Markovitch: Multiple-Goal Heuristic Search. J. Artif. Intell. Res. (JAIR) 26: 417-451 (2006)
39		Asaf Amit, Shaul Markovitch: Learning to bid in bridge. Machine Learning 63(3): 287-327 (2006)
	2005
38		Evgeniy Gabrilovich, Shaul Markovitch: Feature Generation for Text Categorization Using World Knowledge. IJCAI 2005: 1048-1053
37		Yaniv Hamo, Shaul Markovitch: The COMPSET Algorithm for Subset Selection. IJCAI 2005: 728-733
36		Shaul Markovitch, Ronit Reger: Learning and Exploiting Relative Weaknesses of Opponent Agents. Autonomous Agents and Multi-Agent Systems 10(2): 103-130 (2005)
	2004
35		Saher Esmeir, Shaul Markovitch: Lookahead-based algorithms for anytime induction of decision trees. ICML 2004
34		Evgeniy Gabrilovich, Shaul Markovitch: Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5. ICML 2004
33		Dmitry Davidov, Evgeniy Gabrilovich, Shaul Markovitch: Parameterized generation of labeled datasets for text categorization based on a hierarchical directory. SIGIR 2004: 250-257
32		Michael Lindenbaum, Shaul Markovitch, Dmitry Rusakov: Selective Sampling for Nearest Neighbor Classifiers. Machine Learning 54(2): 125-152 (2004)
	2003
31		Orna Grumberg, Shlomi Livne, Shaul Markovitch: Learning to Order BDD Variables in Verification. J. Artif. Intell. Res. (JAIR) 18: 83-116 (2003)
30		Lev Finkelstein, Shaul Markovitch, Ehud Rivlin: Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Shared Resources. J. Artif. Intell. Res. (JAIR) 19: 73-138 (2003)
29		Shaul Markovitch, Asaf Shatil: Speedup Learning for Repair-based Search by Identifying Redundant Steps. Journal of Machine Learning Research 4: 649-682 (2003)
	2002
28		Dmitry Davidov, Shaul Markovitch: Multiple-Goal Search Algorithms and their Application to Web Crawling. AAAI/IAAI 2002: 713-718
27		Lev Finkelstein, Shaul Markovitch, Ehud Rivlin: Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Independent Processes. AAAI/IAAI 2002: 719-724
26		Shaul Markovitch, Dan Rosenstein: Feature Generation Using General Constructor Functions. Machine Learning 49(1): 59-98 (2002)
	2001
25		Lev Finkelstein, Shaul Markovitch: Optimal schedules for monitoring anytime algorithms. Artif. Intell. 126(1-2): 63-108 (2001)
	1999
24		Michael Lindenbaum, Shaul Markovitch, Dmitry Rusakov: Selective Sampling for Nearest Neighbor Classifiers. AAAI/IAAI 1999: 366-371
23		David Carmel, Shaul Markovitch: Exploration Strategies for Model-based Learning in Multi-agent Systems: Exploration Strategies. Autonomous Agents and Multi-Agent Systems 2(2): 141-172 (1999)
	1998
22		Oleg Ledeniov, Shaul Markovitch: Learning Investment Functions for Controlling the Utility of Control Knowledge. AAAI/IAAI 1998: 463-468
21		David Carmel, Shaul Markovitch: How to Explore your Opponent's Strategy (almost) Optimally. ICMAS 1998: 64-71
20		David Carmel, Shaul Markovitch: Pruning Algorithms for Multi-Model Adversary Search. Artif. Intell. 99(2): 325-355 (1998)
19		Lev Finkelstein, Shaul Markovitch: A Selective Macro-learning Algorithm and its Application to the NxN Sliding-Tile Puzzle CoRR cs.AI/9806102: (1998)
18		Lev Finkelstein, Shaul Markovitch: A Selective Macro-learning Algorithm and its Application to the NxN Sliding-Tile Puzzle. J. Artif. Intell. Res. (JAIR) 8: 223-263 (1998)
17		Oleg Ledeniov, Shaul Markovitch: The Divide-and-Conquer Subgoal-Ordering Algorithm for Speeding up Logic Inference. J. Artif. Intell. Res. (JAIR) 9: 37-97 (1998)
16		David Carmel, Shaul Markovitch: Model-based learning of interaction strategies in multi-agent systems. J. Exp. Theor. Artif. Intell. 10(3): 309-332 (1998)
	1997
15		David Carmel, Shaul Markovitch: Exploration and Adaptation in Multiagent Systems: A Model-based Approach. IJCAI (1) 1997: 606-611
	1996
14		David Carmel, Shaul Markovitch: Incorporating Opponent Models into Adversary Search. AAAI/IAAI, Vol. 1 1996: 120-125
13		David Carmel, Shaul Markovitch: Learning Models of Intelligent Agents. AAAI/IAAI, Vol. 1 1996: 62-67
12		Shaul Markovitch, Yaron Sella: Learning of Resource Allocation Strategies for Game Playing. Computational Intelligence 12: 88-105 (1996)
	1995
11		David Carmel, Shaul Markovitch: Opponent Modeling in Multi-Agent Systems. Adaption and Learning in Multi-Agent Systems 1995: 40-52
	1993
10		Ido Dagan, Shaul Marcus, Shaul Markovitch: Contextual Word Similarity and Estimation from Sparse Data. ACL 1993: 164-171
9		Shaul Markovitch, Yaron Sella: Learning of Resource Allocation Strategies for Game Playing. IJCAI 1993: 974-979
8		Shaul Markovitch, Paul D. Scott: Information Filtering: Selection Mechanisms in Learning Systems. Machine Learning 10: 113-151 (1993)
7		Paul D. Scott, Shaul Markovitch: Experience Selection and Problem Choice in an Exploratory Learning System. Machine Learning 12: 49-67 (1993)
	1989
6		Paul D. Scott, Shaul Markovitch: Learning Novel Domains Through Curiosity and Conjecture. IJCAI 1989: 669-674
5		Shaul Markovitch, Paul D. Scott: Utilization Filtering: A Method for Reducing the Inherent Harmfulness of Deductively Learned Knowledge. IJCAI 1989: 738-743
4		Paul D. Scott, Shaul Markovitch: Uncertainty Based Selection of Learning Experiences. ML 1989: 358-361
3		Shaul Markovitch, Paul D. Scott: Information Filters and Their Implementation in the SYLLOG System. ML 1989: 404-407
2		Shaul Markovitch, Paul D. Scott: Automatic Ordering of Subgoals - A Machine Learning Approach. NACLP 1989: 224-240
	1988
1		Shaul Markovitch, Paul D. Scott: The Role of Forgetting in Learning. ML 1988: 459-465

Coauthor Index

1	Asaf Amit	[39]
2	David Carmel	[11] [13] [14] [15] [16] [20] [21] [23]
3	Ido Dagan	[10]
4	Dmitry Davidov	[28] [33] [40]
5	Sagie Davidovich	[49]
6	Ofer Egozi	[50]
7	Saher Esmeir	[35] [41] [43] [45] [46] [48]
8	Lev Finkelstein	[18] [19] [25] [27] [30]
9	Evgeniy Gabrilovich	[33] [34] [38] [42] [47] [50] [51]
10	Orna Grumberg	[31]
11	Nela Gurevich	[44]
12	Yaniv Hamo	[37]
13	Oleg Ledeniov	[17] [22]
14	Michael Lindenbaum	[24] [32]
15	Shlomi Livne	[31]
16	Shaul Marcus	[10]
17	Kira Radinsky	[49]
18	Ronit Reger	[36]
19	Ehud Rivlin	[27] [30] [44]
20	Dan Rosenstein	[26]
21	Dmitry Rusakov	[24] [32]
22	Paul D. Scott	[1] [2] [3] [4] [5] [6] [7] [8]
23	Yaron Sella	[9] [12]
24	Asaf Shatil	[29]

Colors in the list of coauthors