Shaul Markovitch

Publication Activity (10 Years)

Years Active: 1988-2024
Publications (10 Years): 14

Top Topics

Named Entity Disambiguation

Embedding Space

Feature Generation

Optimal Planning

Top Venues

Publications

Daniel Gilo, Shaul Markovitch
A General Search-Based Framework for Generating Textual Counterfactual Explanations. AAAI (2024)
Adi Simhi, Shaul Markovitch
Interpreting Embedding Spaces by Conceptualization. EMNLP (2023)
Daniel Gilo, Shaul Markovitch
Anytime Generation of Counterfactual Explanations for Text Classification. CoRR (2022)
Adi Simhi, Shaul Markovitch
Interpreting Embedding Spaces by Conceptualization. CoRR (2022)
Guy Kushilevitz, Shaul Markovitch, Yoav Goldberg
A Two-Stage Masked LM Method for Term Set Expansion. CoRR (2020)
Guy Kushilevitz, Shaul Markovitch, Yoav Goldberg
A Two-Stage Masked LM Method for Term Set Expansion. ACL (2020)
Michal Badian, Shaul Markovitch
Knowledge-Based Learning through Feature Generation. CoRR (2020)
Jonathan Zarecki, Shaul Markovitch
Textual Membership Queries. IJCAI (2020)
Nurit Devir, Orna Grumberg, Shaul Markovitch, Gabi Nakibly
Topology-Agnostic Runtime Detection of OSPF Routing Attacks. CNS (2019)
Jonathan Zarecki, Shaul Markovitch
Textual Membership Queries. CoRR (2018)
Sarai Duek, Shaul Markovitch
Automatic Generation of Language-Independent Features for Cross-Lingual Classification. CoRR (2018)
Lior Friedman, Shaul Markovitch
Recursive Feature Generation for Knowledge-based Learning. CoRR (2018)
Yotam Eshel, Noam Cohen, Kira Radinsky, Shaul Markovitch, Ikuya Yamada, Omer Levy
Named Entity Disambiguation for Noisy Text. CoRR (2017)
Yotam Eshel, Noam Cohen, Kira Radinsky, Shaul Markovitch, Ikuya Yamada, Omer Levy
Named Entity Disambiguation for Noisy Text. CoNLL (2017)
Omer Geiger, Shaul Markovitch
Algorithmic Exam Generation. IJCAI (2015)
Kira Radinsky, Sagie Davidovich, Shaul Markovitch
Learning to Predict from Textual Data. CoRR (2014)
Evgeniy Gabrilovich, Shaul Markovitch
Wikipedia-based Semantic Interpretation for Natural Language Processing. CoRR (2014)
Carmel Domshlak, Erez Karpas, Shaul Markovitch
Online Speedup Learning for Optimal Planning. CoRR (2014)
Assaf Glazer, Omer Weissbrod, Michael Lindenbaum, Shaul Markovitch
Approximating Hierarchical MV-sets for Hierarchical Clustering. NIPS (2014)
Saher Esmeir, Shaul Markovitch
Anytime Induction of Low-cost, Low-error Classifiers: a Sampling-based Approach. CoRR (2014)
Assaf Glazer, Michael Lindenbaum, Shaul Markovitch
q-OCSVM: A q-Quantile Estimator for High-Dimensional Distributions. NIPS (2013)
Assaf Glazer, Michael Lindenbaum, Shaul Markovitch
Feature shift detection. ICPR (2012)
Tamar Avraham, Ilya Gurvich, Michael Lindenbaum, Shaul Markovitch
Learning Implicit Transfer for Person Re-identification. ECCV Workshops (1) (2012)
Assaf Glazer, Michael Lindenbaum, Shaul Markovitch
Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data. NIPS (2012)
Assaf Glazer, Michael Lindenbaum, Shaul Markovitch
One-Class Background Model. ACCV Workshops (1) (2012)
Omer Levy, Shaul Markovitch
Teaching Machines to Learn by Metaphors. AAAI (2012)
Carmel Domshlak, Erez Karpas, Shaul Markovitch
Online Speedup Learning for Optimal Planning. J. Artif. Intell. Res. 44 (2012)
Kira Radinsky, Sagie Davidovich, Shaul Markovitch
Learning to Predict from Textual Data. J. Artif. Intell. Res. 45 (2012)
Ariel Raviv, Shaul Markovitch
Concept-Based Approach to Word-Sense Disambiguation. AAAI (2012)
Kira Radinsky, Sagie Davidovich, Shaul Markovitch
Learning causality for news events prediction. WWW (2012)
Dmitry Davidov, Shaul Markovitch
Multiple-Goal Heuristic Search CoRR (2011)
Kira Radinsky, Eugene Agichtein, Evgeniy Gabrilovich, Shaul Markovitch
A word at a time: computing word relatedness using temporal semantic analysis. WWW (2011)
Lev Finkelstein, Shaul Markovitch, Ehud Rivlin
Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Shared Resources CoRR (2011)
Orna Grumberg, Shlomi Livne, Shaul Markovitch
Learning to Order BDD Variables in Verification CoRR (2011)
Anat Hashavit, Shaul Markovitch
Max-Prob: An Unbiased Rational Decision Making Procedure for Multiple-Adversary Environments. IJCAI (2011)
Saher Esmeir, Shaul Markovitch
Anytime learning of anycost classifiers. Mach. Learn. 82 (3) (2011)
Ofer Egozi, Shaul Markovitch, Evgeniy Gabrilovich
Concept-Based Information Retrieval Using Explicit Semantic Analysis. ACM Trans. Inf. Syst. 29 (2) (2011)
Erez Karpas, Michael Katz, Shaul Markovitch
When Optimal Is Just Not Good Enough: Learning Fast Informative Action Cost Partitionings. ICAPS (2011)
Oleg Ledeniov, Shaul Markovitch
The Divide-and-Conquer Subgoal-Ordering Algorithm for Speeding up Logic Inference CoRR (2011)
Carmel Domshlak, Erez Karpas, Shaul Markovitch
To Max or Not to Max: Online Learning for Speeding Up Optimal Planning. AAAI (2010)
Evgeniy Gabrilovich, Shaul Markovitch
Wikipedia-based Semantic Interpretation for Natural Language Processing. J. Artif. Intell. Res. 34 (2009)
Kira Radinsky, Sagie Davidovich, Shaul Markovitch
Predicting theNews of Tomorrow Using Patterns in Web Search Queries. Web Intelligence (2008)
Ofer Egozi, Evgeniy Gabrilovich, Shaul Markovitch
Concept-Based Feature Generation and Selection for Information Retrieval. AAAI (2008)
Saher Esmeir, Shaul Markovitch
Anytime Induction of Low-cost, Low-error Classifiers: a Sampling-based Approach. J. Artif. Intell. Res. 33 (2008)
Saher Esmeir, Shaul Markovitch
Occam's Razor Just Got Sharper. IJCAI (2007)
Evgeniy Gabrilovich, Shaul Markovitch
Computing Semantic Relatedness Using Wikipedia-based Explicit Semantic Analysis. IJCAI (2007)
Saher Esmeir, Shaul Markovitch
Anytime Learning of Decision Trees. J. Mach. Learn. Res. 8 (2007)
Evgeniy Gabrilovich, Shaul Markovitch
Harnessing the Expertise of 70, 000 Human Editors: Knowledge-Based Feature Generation for Text Categorization. J. Mach. Learn. Res. 8 (2007)
Saher Esmeir, Shaul Markovitch
Anytime Induction of Cost-sensitive Trees. NIPS (2007)
Dmitry Davidov, Shaul Markovitch
Multiple-Goal Heuristic Search. J. Artif. Intell. Res. 26 (2006)
Evgeniy Gabrilovich, Shaul Markovitch
Overcoming the Brittleness Bottleneck using Wikipedia: Enhancing Text Categorization with Encyclopedic Knowledge. AAAI (2006)
Asaf Amit, Shaul Markovitch
Learning to bid in bridge. Mach. Learn. 63 (3) (2006)
Saher Esmeir, Shaul Markovitch
When a Decision Tree Learner Has Plenty of Time. AAAI (2006)
Saher Esmeir, Shaul Markovitch
Anytime Induction of Decision Trees: An Iterative Improvement Approach. AAAI (2006)
Nela Gurevich, Shaul Markovitch, Ehud Rivlin
Active Learning with Near Misses. AAAI (2006)
Shaul Markovitch, Ronit Reger
Learning and Exploiting Relative Weaknesses of Opponent Agents. Auton. Agents Multi Agent Syst. 10 (2) (2005)
Yaniv Hamo, Shaul Markovitch
The COMPSET Algorithm for Subset Selection. IJCAI (2005)
Evgeniy Gabrilovich, Shaul Markovitch
Feature Generation for Text Categorization Using World Knowledge. IJCAI (2005)
Evgeniy Gabrilovich, Shaul Markovitch
Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5. ICML (2004)
Dmitry Davidov, Evgeniy Gabrilovich, Shaul Markovitch
Parameterized generation of labeled datasets for text categorization based on a hierarchical directory. SIGIR (2004)
Saher Esmeir, Shaul Markovitch
Lookahead-based algorithms for anytime induction of decision trees. ICML (2004)
Michael Lindenbaum, Shaul Markovitch, Dmitry Rusakov
Selective Sampling for Nearest Neighbor Classifiers. Mach. Learn. 54 (2) (2004)
Lev Finkelstein, Shaul Markovitch, Ehud Rivlin
Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Shared Resources. J. Artif. Intell. Res. 19 (2003)
Shaul Markovitch, Asaf Shatil
Speedup Learning for Repair-based Search by Identifying Redundant Steps. J. Mach. Learn. Res. 4 (2003)
Orna Grumberg, Shlomi Livne, Shaul Markovitch
Learning to Order BDD Variables in Verification. J. Artif. Intell. Res. 18 (2003)
Dmitry Davidov, Shaul Markovitch
Multiple-Goal Search Algorithms and their Application to Web Crawling. AAAI/IAAI (2002)
Shaul Markovitch, Dan Rosenstein
Feature Generation Using General Constructor Functions. Mach. Learn. 49 (1) (2002)
Lev Finkelstein, Shaul Markovitch, Ehud Rivlin
Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Independent Processes. AAAI/IAAI (2002)
Lev Finkelstein, Shaul Markovitch
Optimal schedules for monitoring anytime algorithms. Artif. Intell. 126 (1-2) (2001)
Michael Lindenbaum, Shaul Markovitch, Dmitry Rusakov
Selective Sampling for Nearest Neighbor Classifiers. AAAI/IAAI (1999)
David Carmel, Shaul Markovitch
Exploration Strategies for Model-based Learning in Multi-agent Systems: Exploration Strategies. Auton. Agents Multi Agent Syst. 2 (2) (1999)
Lev Finkelstein, Shaul Markovitch
A Selective Macro-learning Algorithm and its Application to the NxN Sliding-Tile Puzzle. J. Artif. Intell. Res. 8 (1998)
Lev Finkelstein, Shaul Markovitch
Learning to Play Chess Selectively by Acquiring Move Patterns. J. Int. Comput. Games Assoc. 21 (2) (1998)
David Carmel, Shaul Markovitch
Pruning Algorithms for Multi-model Adversary Search. J. Int. Comput. Games Assoc. 21 (3) (1998)
Lev Finkelstein, Shaul Markovitch
A Selective Macro-learning Algorithm and its Application to the NxN Sliding-Tile Puzzle CoRR (1998)
David Carmel, Shaul Markovitch
How to Explore your Opponent's Strategy (almost) Optimally. ICMAS (1998)
David Carmel, Shaul Markovitch
Pruning Algorithms for Multi-Model Adversary Search. Artif. Intell. 99 (2) (1998)
Oleg Ledeniov, Shaul Markovitch
Learning Investment Functions for Controlling the Utility of Control Knowledge. AAAI/IAAI (1998)
David Carmel, Shaul Markovitch
Model-based learning of interaction strategies in multi-agent systems. J. Exp. Theor. Artif. Intell. 10 (3) (1998)
Oleg Ledeniov, Shaul Markovitch
The Divide-and-Conquer Subgoal-Ordering Algorithm for Speeding up Logic Inference. J. Artif. Intell. Res. 9 (1998)
David Carmel, Shaul Markovitch
Exploration and Adaptation in Multiagent Systems: A Model-based Approach. IJCAI (1) (1997)
David Carmel, Shaul Markovitch
Learning Models of Intelligent Agents. AAAI/IAAI, Vol. 1 (1996)
David Carmel, Shaul Markovitch
Incorporating Opponent Models into Adversary Search. AAAI/IAAI, Vol. 1 (1996)
Shaul Markovitch, Yaron Sella
Learning of Resource Allocation Strategies for Game Playing. Comput. Intell. 12 (1996)
Ido Dagan, Shaul Marcus, Shaul Markovitch
Contextual word similarity and estimation from sparse data. Comput. Speech Lang. 9 (2) (1995)
David Carmel, Shaul Markovitch
Opponent Modeling in Multi-Agent Systems. Adaption and Learning in Multi-Agent Systems (1995)
Shaul Markovitch, Paul D. Scott
Information Filtering: Selection Mechanisms in Learning Systems. Mach. Learn. 10 (1993)
Shaul Markovitch, Yaron Sella
Learning of Resource Allocation Strategies for Game Playing. IJCAI (1993)
Ido Dagan, Shaul Marcus, Shaul Markovitch
Contextual Word Similarity and Estimation from Sparse Data. ACL (1993)
Paul D. Scott, Shaul Markovitch
Experience Selection and Problem Choice in an Exploratory Learning System. Mach. Learn. 12 (1993)
Paul D. Scott, Shaul Markovitch
Learning Novel Domains Through Curiosity and Conjecture. IJCAI (1989)
Shaul Markovitch, Paul D. Scott
Utilization Filtering: A Method for Reducing the Inherent Harmfulness of Deductively Learned Knowledge. IJCAI (1989)
Shaul Markovitch, Paul D. Scott
Information Filters and Their Implementation in the SYLLOG System. ML (1989)
Shaul Markovitch, Paul D. Scott
Automatic Ordering of Subgoals - A Machine Learning Approach. NACLP (1989)
Paul D. Scott, Shaul Markovitch
Uncertainty Based Selection of Learning Experiences. ML (1989)
Shaul Markovitch, Paul D. Scott
The Role of Forgetting in Learning. ML (1988)