Shaul Markovitch

According to our database, Shaul Markovitch authored at least 80 papers between 1988 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

A General Search-Based Framework for Generating Textual Counterfactual Explanations.

Daniel Gilo, Shaul Markovitch

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Interpreting Embedding Spaces by Conceptualization.

Adi Simhi, Shaul Markovitch

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022

Anytime Generation of Counterfactual Explanations for Text Classification.

Daniel Gilo, Shaul Markovitch

CoRR, 2022

2020

Knowledge-Based Learning through Feature Generation.

Michal Badian, Shaul Markovitch

CoRR, 2020

Textual Membership Queries.

Jonathan Zarecki, Shaul Markovitch

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

A Two-Stage Masked LM Method for Term Set Expansion.

Guy Kushilevitz, Shaul Markovitch, Yoav Goldberg

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Topology-Agnostic Runtime Detection of OSPF Routing Attacks.

Nurit Devir, Orna Grumberg, Shaul Markovitch, Gabi Nakibly

Proceedings of the 7th IEEE Conference on Communications and Network Security, 2019

2018

Automatic Generation of Language-Independent Features for Cross-Lingual Classification.

Sarai Duek, Shaul Markovitch

CoRR, 2018

Recursive Feature Generation for Knowledge-based Learning.

Lior Friedman, Shaul Markovitch

CoRR, 2018

2017

Named Entity Disambiguation for Noisy Text.

Yotam Eshel, Noam Cohen, Kira Radinsky, Shaul Markovitch, Ikuya Yamada, Omer Levy

Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), 2017

2015

Algorithmic Exam Generation.

Omer Geiger, Shaul Markovitch

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015

2014

Approximating Hierarchical MV-sets for Hierarchical Clustering.

Assaf Glazer, Omer Weissbrod, Michael Lindenbaum, Shaul Markovitch

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

q-OCSVM: A q-Quantile Estimator for High-Dimensional Distributions.

Assaf Glazer, Michael Lindenbaum, Shaul Markovitch

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012

Learning to Predict from Textual Data.

Kira Radinsky, Sagie Davidovich, Shaul Markovitch

J. Artif. Intell. Res., 2012

Online Speedup Learning for Optimal Planning.

Carmel Domshlak, Erez Karpas, Shaul Markovitch

J. Artif. Intell. Res., 2012

Learning causality for news events prediction.

Kira Radinsky, Sagie Davidovich, Shaul Markovitch

Proceedings of the 21st World Wide Web Conference 2012, 2012

Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data.

Assaf Glazer, Michael Lindenbaum, Shaul Markovitch

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Feature shift detection.

Assaf Glazer, Michael Lindenbaum, Shaul Markovitch

Proceedings of the 21st International Conference on Pattern Recognition, 2012

Learning Implicit Transfer for Person Re-identification.

Tamar Avraham, Ilya Gurvich, Michael Lindenbaum, Shaul Markovitch

Proceedings of the Computer Vision - ECCV 2012. Workshops and Demonstrations, 2012

One-Class Background Model.

Assaf Glazer, Michael Lindenbaum, Shaul Markovitch

Proceedings of the Computer Vision - ACCV 2012 Workshops, 2012

Concept-Based Approach to Word-Sense Disambiguation.

Ariel Raviv, Shaul Markovitch

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

Teaching Machines to Learn by Metaphors.

Omer Levy, Shaul Markovitch

Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence, 2012

2011

Concept-Based Information Retrieval Using Explicit Semantic Analysis.

Ofer Egozi, Shaul Markovitch, Evgeniy Gabrilovich

ACM Trans. Inf. Syst., 2011

Anytime learning of anycost classifiers.

Saher Esmeir, Shaul Markovitch

Mach. Learn., 2011

A word at a time: computing word relatedness using temporal semantic analysis.

Kira Radinsky, Eugene Agichtein, Evgeniy Gabrilovich, Shaul Markovitch

Proceedings of the 20th International Conference on World Wide Web, 2011

Max-Prob: An Unbiased Rational Decision Making Procedure for Multiple-Adversary Environments.

Anat Hashavit, Shaul Markovitch

Proceedings of the IJCAI 2011, 2011

When Optimal Is Just Not Good Enough: Learning Fast Informative Action Cost Partitionings.

Erez Karpas, Michael Katz, Shaul Markovitch

Proceedings of the 21st International Conference on Automated Planning and Scheduling, 2011

2010

To Max or Not to Max: Online Learning for Speeding Up Optimal Planning.

Carmel Domshlak, Erez Karpas, Shaul Markovitch

Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, 2010

2009

Wikipedia-based Semantic Interpretation for Natural Language Processing.

Evgeniy Gabrilovich, Shaul Markovitch

J. Artif. Intell. Res., 2009

2008

Anytime Induction of Low-cost, Low-error Classifiers: a Sampling-based Approach.

Saher Esmeir, Shaul Markovitch

J. Artif. Intell. Res., 2008

Predicting theNews of Tomorrow Using Patterns in Web Search Queries.

Kira Radinsky, Sagie Davidovich, Shaul Markovitch

Proceedings of the 2008 IEEE / WIC / ACM International Conference on Web Intelligence, 2008

Concept-Based Feature Generation and Selection for Information Retrieval.

Ofer Egozi, Evgeniy Gabrilovich, Shaul Markovitch

Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence, 2008

2007

Harnessing the Expertise of 70, 000 Human Editors: Knowledge-Based Feature Generation for Text Categorization.

Evgeniy Gabrilovich, Shaul Markovitch

J. Mach. Learn. Res., 2007

Anytime Learning of Decision Trees.

Saher Esmeir, Shaul Markovitch

J. Mach. Learn. Res., 2007

Anytime Induction of Cost-sensitive Trees.

Saher Esmeir, Shaul Markovitch

Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Computing Semantic Relatedness Using Wikipedia-based Explicit Semantic Analysis.

Evgeniy Gabrilovich, Shaul Markovitch

Proceedings of the IJCAI 2007, 2007

Occam's Razor Just Got Sharper.

Saher Esmeir, Shaul Markovitch

Proceedings of the IJCAI 2007, 2007

2006

Learning to bid in bridge.

Asaf Amit, Shaul Markovitch

Mach. Learn., 2006

Multiple-Goal Heuristic Search.

Dmitry Davidov, Shaul Markovitch

J. Artif. Intell. Res., 2006

Active Learning with Near Misses.

Nela Gurevich, Shaul Markovitch, Ehud Rivlin

Proceedings of the Proceedings, 2006

Overcoming the Brittleness Bottleneck using Wikipedia: Enhancing Text Categorization with Encyclopedic Knowledge.

Evgeniy Gabrilovich, Shaul Markovitch

Proceedings of the Proceedings, 2006

When a Decision Tree Learner Has Plenty of Time.

Saher Esmeir, Shaul Markovitch

Proceedings of the Proceedings, 2006

Anytime Induction of Decision Trees: An Iterative Improvement Approach.

Saher Esmeir, Shaul Markovitch

Proceedings of the Proceedings, 2006

2005

Learning and Exploiting Relative Weaknesses of Opponent Agents.

Shaul Markovitch, Ronit Reger

Auton. Agents Multi Agent Syst., 2005

The COMPSET Algorithm for Subset Selection.

Yaniv Hamo, Shaul Markovitch

Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

Feature Generation for Text Categorization Using World Knowledge.

Evgeniy Gabrilovich, Shaul Markovitch

Proceedings of the IJCAI-05, Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence, Edinburgh, Scotland, UK, July 30, 2005

2004

Selective Sampling for Nearest Neighbor Classifiers.

Michael Lindenbaum, Shaul Markovitch, Dmitry Rusakov

Mach. Learn., 2004

Parameterized generation of labeled datasets for text categorization based on a hierarchical directory.

Dmitry Davidov, Evgeniy Gabrilovich, Shaul Markovitch

Proceedings of the SIGIR 2004: Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2004

Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5.

Evgeniy Gabrilovich, Shaul Markovitch

Proceedings of the Machine Learning, 2004

Lookahead-based algorithms for anytime induction of decision trees.

Saher Esmeir, Shaul Markovitch

Proceedings of the Machine Learning, 2004

2003

Speedup Learning for Repair-based Search by Identifying Redundant Steps.

Shaul Markovitch, Asaf Shatil

J. Mach. Learn. Res., 2003

Learning to Order BDD Variables in Verification.

Orna Grumberg, Shlomi Livne, Shaul Markovitch

J. Artif. Intell. Res., 2003

Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Shared Resources.

Lev Finkelstein, Shaul Markovitch, Ehud Rivlin

J. Artif. Intell. Res., 2003

2002

Feature Generation Using General Constructor Functions.

Shaul Markovitch, Dan Rosenstein

Mach. Learn., 2002

Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Independent Processes.

Lev Finkelstein, Shaul Markovitch, Ehud Rivlin

Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002

Multiple-Goal Search Algorithms and their Application to Web Crawling.

Dmitry Davidov, Shaul Markovitch

Proceedings of the Eighteenth National Conference on Artificial Intelligence and Fourteenth Conference on Innovative Applications of Artificial Intelligence, July 28, 2002

2001

Optimal schedules for monitoring anytime algorithms.

Lev Finkelstein, Shaul Markovitch

Artif. Intell., 2001

1999

Exploration Strategies for Model-based Learning in Multi-agent Systems: Exploration Strategies.

David Carmel, Shaul Markovitch

Auton. Agents Multi Agent Syst., 1999

1998

Model-based learning of interaction strategies in multi-agent systems.

David Carmel, Shaul Markovitch

J. Exp. Theor. Artif. Intell., 1998

The Divide-and-Conquer Subgoal-Ordering Algorithm for Speeding up Logic Inference.

Oleg Ledeniov, Shaul Markovitch

J. Artif. Intell. Res., 1998

A Selective Macro-learning Algorithm and its Application to the NxN Sliding-Tile Puzzle.

Lev Finkelstein, Shaul Markovitch

J. Artif. Intell. Res., 1998

Learning to Play Chess Selectively by Acquiring Move Patterns.

Lev Finkelstein, Shaul Markovitch

J. Int. Comput. Games Assoc., 1998

Pruning Algorithms for Multi-model Adversary Search.

David Carmel, Shaul Markovitch

J. Int. Comput. Games Assoc., 1998

How to Explore your Opponent's Strategy (almost) Optimally.

David Carmel, Shaul Markovitch

Proceedings of the Third International Conference on Multiagent Systems, 1998

Learning Investment Functions for Controlling the Utility of Control Knowledge.

Oleg Ledeniov, Shaul Markovitch

Proceedings of the Fifteenth National Conference on Artificial Intelligence and Tenth Innovative Applications of Artificial Intelligence Conference, 1998

1997

Exploration and Adaptation in Multiagent Systems: A Model-based Approach.

David Carmel, Shaul Markovitch

Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence, 1997

1996

Learning of Resource Allocation Strategies for Game Playing.

Shaul Markovitch, Yaron Sella

Comput. Intell., 1996

Incorporating Opponent Models into Adversary Search.

David Carmel, Shaul Markovitch

Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996

Learning Models of Intelligent Agents.

David Carmel, Shaul Markovitch

Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996

1995

Contextual word similarity and estimation from sparse data.

Ido Dagan, Shaul Marcus, Shaul Markovitch

Comput. Speech Lang., 1995

Opponent Modeling in Multi-Agent Systems.

David Carmel, Shaul Markovitch

Proceedings of the Adaption and Learning in Multi-Agent Systems, 1995

1993

Experience Selection and Problem Choice in an Exploratory Learning System.

Paul D. Scott, Shaul Markovitch

Mach. Learn., 1993

Information Filtering: Selection Mechanisms in Learning Systems.

Shaul Markovitch, Paul D. Scott

Mach. Learn., 1993

1989

Information filtering: Selection mechanisms in learning systems.

Shaul Markovitch

PhD thesis, 1989

Automatic Ordering of Subgoals - A Machine Learning Approach.

Shaul Markovitch, Paul D. Scott

Proceedings of the Logic Programming, 1989

Learning Novel Domains Through Curiosity and Conjecture.

Paul D. Scott, Shaul Markovitch

Proceedings of the 11th International Joint Conference on Artificial Intelligence. Detroit, 1989

Utilization Filtering: A Method for Reducing the Inherent Harmfulness of Deductively Learned Knowledge.

Shaul Markovitch, Paul D. Scott

Proceedings of the 11th International Joint Conference on Artificial Intelligence. Detroit, 1989

Uncertainty Based Selection of Learning Experiences.

Paul D. Scott, Shaul Markovitch

Proceedings of the Sixth International Workshop on Machine Learning (ML 1989), 1989

Information Filters and Their Implementation in the SYLLOG System.

Shaul Markovitch, Paul D. Scott

Proceedings of the Sixth International Workshop on Machine Learning (ML 1989), 1989

1988

The Role of Forgetting in Learning.

Shaul Markovitch, Paul D. Scott

Proceedings of the Machine Learning, 1988