| 2008 |
|---|
| 49 | | Ofer Egozi,
Evgeniy Gabrilovich,
Shaul Markovitch:
Concept-Based Feature Generation and Selection for Information Retrieval.
AAAI 2008: 1132-1137 |
| 48 | EE | Kira Radinsky,
Sagie Davidovich,
Shaul Markovitch:
Predicting theNews of Tomorrow Using Patterns in Web Search Queries.
Web Intelligence 2008: 363-367 |
| 2007 |
|---|
| 47 | EE | Evgeniy Gabrilovich,
Shaul Markovitch:
Computing Semantic Relatedness Using Wikipedia-based Explicit Semantic Analysis.
IJCAI 2007: 1606-1611 |
| 46 | EE | Saher Esmeir,
Shaul Markovitch:
Occam's Razor Just Got Sharper.
IJCAI 2007: 768-773 |
| 45 | EE | 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 | EE | Dmitry Davidov,
Shaul Markovitch:
Multiple-Goal Heuristic Search.
J. Artif. Intell. Res. (JAIR) 26: 417-451 (2006) |
| 39 | EE | Asaf Amit,
Shaul Markovitch:
Learning to bid in bridge.
Machine Learning 63(3): 287-327 (2006) |
| 2005 |
|---|
| 38 | EE | Evgeniy Gabrilovich,
Shaul Markovitch:
Feature Generation for Text Categorization Using World Knowledge.
IJCAI 2005: 1048-1053 |
| 37 | EE | Yaniv Hamo,
Shaul Markovitch:
The COMPSET Algorithm for Subset Selection.
IJCAI 2005: 728-733 |
| 36 | EE | 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 | EE | Saher Esmeir,
Shaul Markovitch:
Lookahead-based algorithms for anytime induction of decision trees.
ICML 2004 |
| 34 | EE | Evgeniy Gabrilovich,
Shaul Markovitch:
Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5.
ICML 2004 |
| 33 | EE | Dmitry Davidov,
Evgeniy Gabrilovich,
Shaul Markovitch:
Parameterized generation of labeled datasets for text categorization based on a hierarchical directory.
SIGIR 2004: 250-257 |
| 32 | EE | Michael Lindenbaum,
Shaul Markovitch,
Dmitry Rusakov:
Selective Sampling for Nearest Neighbor Classifiers.
Machine Learning 54(2): 125-152 (2004) |
| 2003 |
|---|
| 31 | EE | Orna Grumberg,
Shlomi Livne,
Shaul Markovitch:
Learning to Order BDD Variables in Verification.
J. Artif. Intell. Res. (JAIR) 18: 83-116 (2003) |
| 30 | EE | 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 | EE | 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 | EE | 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 | EE | David Carmel,
Shaul Markovitch:
How to Explore your Opponent's Strategy (almost) Optimally.
ICMAS 1998: 64-71 |
| 20 | EE | David Carmel,
Shaul Markovitch:
Pruning Algorithms for Multi-Model Adversary Search.
Artif. Intell. 99(2): 325-355 (1998) |
| 19 | EE | Lev Finkelstein,
Shaul Markovitch:
A Selective Macro-learning Algorithm and its Application to the NxN Sliding-Tile Puzzle
CoRR cs.AI/9806102: (1998) |
| 18 | EE | 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 | EE | 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 |
