Shaul Markovitch

99 papers A* 29B 2Journal 46Unranked 21

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Concept Layers: Enhancing Interpretability and Intervenability via LLM Conceptualization. CoRR Or Raphael Bidusa, Shaul Markovitch
2024	A*	`conf`	A General Search-Based Framework for Generating Textual Counterfactual Explanations. AAAI Daniel Gilo, Shaul Markovitch
2023	A*	`conf`	Interpreting Embedding Spaces by Conceptualization. EMNLP Adi Simhi, Shaul Markovitch
2022	J	`jnl`	Anytime Generation of Counterfactual Explanations for Text Classification. CoRR Daniel Gilo, Shaul Markovitch
2022	J	`jnl`	Interpreting Embedding Spaces by Conceptualization. CoRR Adi Simhi, Shaul Markovitch
2020	A*	`conf`	A Two-Stage Masked LM Method for Term Set Expansion. ACL Guy Kushilevitz, Shaul Markovitch, Yoav Goldberg
2020	J	`jnl`	A Two-Stage Masked LM Method for Term Set Expansion. CoRR Guy Kushilevitz, Shaul Markovitch, Yoav Goldberg
2020	J	`jnl`	Knowledge-Based Learning through Feature Generation. CoRR Michal Badian, Shaul Markovitch
2020	A*	`conf`	Textual Membership Queries. IJCAI Jonathan Zarecki, Shaul Markovitch
2019	—	`conf`	Topology-Agnostic Runtime Detection of OSPF Routing Attacks. CNS Nurit Devir, Orna Grumberg, Shaul Markovitch, Gabi Nakibly
2018	J	`jnl`	Automatic Generation of Language-Independent Features for Cross-Lingual Classification. CoRR Sarai Duek, Shaul Markovitch
2018	J	`jnl`	Recursive Feature Generation for Knowledge-based Learning. CoRR Lior Friedman, Shaul Markovitch
2018	J	`jnl`	Textual Membership Queries. CoRR Jonathan Zarecki, Shaul Markovitch
2017	B	`conf`	Named Entity Disambiguation for Noisy Text. CoNLL Yotam Eshel, Noam Cohen, Kira Radinsky, Shaul Markovitch, Ikuya Yamada, Omer Levy
2017	J	`jnl`	Named Entity Disambiguation for Noisy Text. CoRR Yotam Eshel, Noam Cohen, Kira Radinsky, Shaul Markovitch, Ikuya Yamada, Omer Levy
2017	A*	`ed.`	Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, February 4-9, 2017, San Francisco, California, USA. AAAI Satinder Singh, Shaul Markovitch
2015	A*	`conf`	Algorithmic Exam Generation. IJCAI Omer Geiger, Shaul Markovitch
2014	J	`jnl`	Anytime Induction of Low-cost, Low-error Classifiers: a Sampling-based Approach. CoRR Saher Esmeir, Shaul Markovitch
2014	—	`conf`	Approximating Hierarchical MV-sets for Hierarchical Clustering. NIPS Assaf Glazer, Omer Weissbrod, Michael Lindenbaum, Shaul Markovitch
2014	J	`jnl`	Learning to Predict from Textual Data. CoRR Kira Radinsky, Sagie Davidovich, Shaul Markovitch
2014	J	`jnl`	Online Speedup Learning for Optimal Planning. CoRR Carmel Domshlak, Erez Karpas, Shaul Markovitch
2014	J	`jnl`	Wikipedia-based Semantic Interpretation for Natural Language Processing. CoRR Evgeniy Gabrilovich, Shaul Markovitch
2013	—	`conf`	q-OCSVM: A q-Quantile Estimator for High-Dimensional Distributions. NIPS Assaf Glazer, Michael Lindenbaum, Shaul Markovitch
2012	A*	`conf`	Concept-Based Approach to Word-Sense Disambiguation. AAAI Ariel Raviv, Shaul Markovitch
2012	B	`conf`	Feature shift detection. ICPR Assaf Glazer, Michael Lindenbaum, Shaul Markovitch
2012	—	`conf`	Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data. NIPS Assaf Glazer, Michael Lindenbaum, Shaul Markovitch
2012	—	`conf`	Learning Implicit Transfer for Person Re-identification. ECCV Workshops (1) Tamar Avraham, Ilya Gurvich, Michael Lindenbaum, Shaul Markovitch
2012	A*	`conf`	Learning causality for news events prediction. WWW Kira Radinsky, Sagie Davidovich, Shaul Markovitch
2012	J	`jnl`	Learning to Predict from Textual Data. J. Artif. Intell. Res. Kira Radinsky, Sagie Davidovich, Shaul Markovitch
2012	—	`conf`	One-Class Background Model. ACCV Workshops (1) Assaf Glazer, Michael Lindenbaum, Shaul Markovitch
2012	J	`jnl`	Online Speedup Learning for Optimal Planning. J. Artif. Intell. Res. Carmel Domshlak, Erez Karpas, Shaul Markovitch
2012	A*	`conf`	Teaching Machines to Learn by Metaphors. AAAI Omer Levy, Shaul Markovitch
2011	A*	`conf`	A word at a time: computing word relatedness using temporal semantic analysis. WWW Kira Radinsky, Eugene Agichtein, Evgeniy Gabrilovich, Shaul Markovitch
2011	J	`jnl`	Anytime learning of anycost classifiers. Mach. Learn. Saher Esmeir, Shaul Markovitch
2011	J	`jnl`	Concept-Based Information Retrieval Using Explicit Semantic Analysis. ACM Trans. Inf. Syst. Ofer Egozi, Shaul Markovitch, Evgeniy Gabrilovich
2011	J	`jnl`	Learning to Order BDD Variables in Verification CoRR Orna Grumberg, Shlomi Livne, Shaul Markovitch
2011	A*	`conf`	Max-Prob: An Unbiased Rational Decision Making Procedure for Multiple-Adversary Environments. IJCAI Anat Hashavit, Shaul Markovitch
2011	J	`jnl`	Multiple-Goal Heuristic Search CoRR Dmitry Davidov, Shaul Markovitch
2011	J	`jnl`	Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Shared Resources CoRR Lev Finkelstein, Shaul Markovitch, Ehud Rivlin
2011	J	`jnl`	The Divide-and-Conquer Subgoal-Ordering Algorithm for Speeding up Logic Inference CoRR Oleg Ledeniov, Shaul Markovitch
2011	A*	`conf`	When Optimal Is Just Not Good Enough: Learning Fast Informative Action Cost Partitionings. ICAPS Erez Karpas, Michael Katz, Shaul Markovitch
2010	A*	`conf`	To Max or Not to Max: Online Learning for Speeding Up Optimal Planning. AAAI Carmel Domshlak, Erez Karpas, Shaul Markovitch
2009	J	`jnl`	Wikipedia-based Semantic Interpretation for Natural Language Processing. J. Artif. Intell. Res. Evgeniy Gabrilovich, Shaul Markovitch
2008	J	`jnl`	Anytime Induction of Low-cost, Low-error Classifiers: a Sampling-based Approach. J. Artif. Intell. Res. Saher Esmeir, Shaul Markovitch
2008	A*	`conf`	Concept-Based Feature Generation and Selection for Information Retrieval. AAAI Ofer Egozi, Evgeniy Gabrilovich, Shaul Markovitch
2008	—	`conf`	Predicting theNews of Tomorrow Using Patterns in Web Search Queries. Web Intelligence Kira Radinsky, Sagie Davidovich, Shaul Markovitch
2007	—	`conf`	Anytime Induction of Cost-sensitive Trees. NIPS Saher Esmeir, Shaul Markovitch
2007	J	`jnl`	Anytime Learning of Decision Trees. J. Mach. Learn. Res. Saher Esmeir, Shaul Markovitch
2007	A*	`conf`	Computing Semantic Relatedness Using Wikipedia-based Explicit Semantic Analysis. IJCAI Evgeniy Gabrilovich, Shaul Markovitch
2007	J	`jnl`	Harnessing the Expertise of 70, 000 Human Editors: Knowledge-Based Feature Generation for Text Categorization. J. Mach. Learn. Res. Evgeniy Gabrilovich, Shaul Markovitch
2007	A*	`conf`	Occam's Razor Just Got Sharper. IJCAI Saher Esmeir, Shaul Markovitch
2006	A*	`conf`	Active Learning with Near Misses. AAAI Nela Gurevich, Shaul Markovitch, Ehud Rivlin
2006	A*	`conf`	Anytime Induction of Decision Trees: An Iterative Improvement Approach. AAAI Saher Esmeir, Shaul Markovitch
2006	J	`jnl`	Learning to bid in bridge. Mach. Learn. Asaf Amit, Shaul Markovitch
2006	J	`jnl`	Multiple-Goal Heuristic Search. J. Artif. Intell. Res. Dmitry Davidov, Shaul Markovitch
2006	A*	`conf`	Overcoming the Brittleness Bottleneck using Wikipedia: Enhancing Text Categorization with Encyclopedic Knowledge. AAAI Evgeniy Gabrilovich, Shaul Markovitch
2006	A*	`conf`	When a Decision Tree Learner Has Plenty of Time. AAAI Saher Esmeir, Shaul Markovitch
2005	A*	`conf`	Feature Generation for Text Categorization Using World Knowledge. IJCAI Evgeniy Gabrilovich, Shaul Markovitch
2005	J	`jnl`	Learning and Exploiting Relative Weaknesses of Opponent Agents. Auton. Agents Multi Agent Syst. Shaul Markovitch, Ronit Reger
2005	A*	`conf`	The COMPSET Algorithm for Subset Selection. IJCAI Yaniv Hamo, Shaul Markovitch
2004	A*	`conf`	Lookahead-based algorithms for anytime induction of decision trees. ICML Saher Esmeir, Shaul Markovitch
2004	A*	`conf`	Parameterized generation of labeled datasets for text categorization based on a hierarchical directory. SIGIR Dmitry Davidov, Evgeniy Gabrilovich, Shaul Markovitch
2004	J	`jnl`	Selective Sampling for Nearest Neighbor Classifiers. Mach. Learn. Michael Lindenbaum, Shaul Markovitch, Dmitry Rusakov
2004	A*	`conf`	Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5. ICML Evgeniy Gabrilovich, Shaul Markovitch
2003	J	`jnl`	Learning to Order BDD Variables in Verification. J. Artif. Intell. Res. Orna Grumberg, Shlomi Livne, Shaul Markovitch
2003	J	`jnl`	Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Shared Resources. J. Artif. Intell. Res. Lev Finkelstein, Shaul Markovitch, Ehud Rivlin
2003	J	`jnl`	Speedup Learning for Repair-based Search by Identifying Redundant Steps. J. Mach. Learn. Res. Shaul Markovitch, Asaf Shatil
2002	J	`jnl`	Feature Generation Using General Constructor Functions. Mach. Learn. Shaul Markovitch, Dan Rosenstein
2002	—	`conf`	Multiple-Goal Search Algorithms and their Application to Web Crawling. AAAI/IAAI Dmitry Davidov, Shaul Markovitch
2002	—	`conf`	Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Independent Processes. AAAI/IAAI Lev Finkelstein, Shaul Markovitch, Ehud Rivlin
2001	J	`jnl`	Optimal schedules for monitoring anytime algorithms. Artif. Intell. Lev Finkelstein, Shaul Markovitch
1999	J	`jnl`	Exploration Strategies for Model-based Learning in Multi-agent Systems: Exploration Strategies. Auton. Agents Multi Agent Syst. David Carmel, Shaul Markovitch
1999	—	`conf`	Selective Sampling for Nearest Neighbor Classifiers. AAAI/IAAI Michael Lindenbaum, Shaul Markovitch, Dmitry Rusakov
1998	J	`jnl`	A Selective Macro-learning Algorithm and its Application to the NxN Sliding-Tile Puzzle CoRR Lev Finkelstein, Shaul Markovitch
1998	J	`jnl`	A Selective Macro-learning Algorithm and its Application to the NxN Sliding-Tile Puzzle. J. Artif. Intell. Res. Lev Finkelstein, Shaul Markovitch
1998	—	`conf`	How to Explore your Opponent's Strategy (almost) Optimally. ICMAS David Carmel, Shaul Markovitch
1998	—	`conf`	Learning Investment Functions for Controlling the Utility of Control Knowledge. AAAI/IAAI Oleg Ledeniov, Shaul Markovitch
1998	J	`jnl`	Learning to Play Chess Selectively by Acquiring Move Patterns. ICCA J. Lev Finkelstein, Shaul Markovitch
1998	J	`jnl`	Model-based learning of interaction strategies in multi-agent systems. J. Exp. Theor. Artif. Intell. David Carmel, Shaul Markovitch
1998	J	`jnl`	Pruning Algorithms for Multi-Model Adversary Search. Artif. Intell. David Carmel, Shaul Markovitch
1998	J	`jnl`	Pruning Algorithms for Multi-model Adversary Search. ICCA J. David Carmel, Shaul Markovitch
1998	J	`jnl`	The Divide-and-Conquer Subgoal-Ordering Algorithm for Speeding up Logic Inference. J. Artif. Intell. Res. Oleg Ledeniov, Shaul Markovitch
1997	—	`conf`	Exploration and Adaptation in Multiagent Systems: A Model-based Approach. IJCAI (1) David Carmel, Shaul Markovitch
1996	—	`conf`	Incorporating Opponent Models into Adversary Search. AAAI/IAAI, Vol. 1 David Carmel, Shaul Markovitch
1996	—	`conf`	Learning Models of Intelligent Agents. AAAI/IAAI, Vol. 1 David Carmel, Shaul Markovitch
1996	J	`jnl`	Learning of Resource Allocation Strategies for Game Playing. Comput. Intell. Shaul Markovitch, Yaron Sella
1995	J	`jnl`	Contextual word similarity and estimation from sparse data. Comput. Speech Lang. Ido Dagan, Shaul Marcus, Shaul Markovitch
1995	—	`conf`	Opponent Modeling in Multi-Agent Systems. Adaption and Learning in Multi-Agent Systems David Carmel, Shaul Markovitch
1993	A*	`conf`	Contextual Word Similarity and Estimation from Sparse Data. ACL Ido Dagan, Shaul Marcus, Shaul Markovitch
1993	J	`jnl`	Experience Selection and Problem Choice in an Exploratory Learning System. Mach. Learn. Paul D. Scott, Shaul Markovitch
1993	J	`jnl`	Information Filtering: Selection Mechanisms in Learning Systems. Mach. Learn. Shaul Markovitch, Paul D. Scott
1993	A*	`conf`	Learning of Resource Allocation Strategies for Game Playing. IJCAI Shaul Markovitch, Yaron Sella
1989	—	`conf`	Automatic Ordering of Subgoals - A Machine Learning Approach. NACLP Shaul Markovitch, Paul D. Scott
1989	—	`conf`	Information Filters and Their Implementation in the SYLLOG System. ML Shaul Markovitch, Paul D. Scott
1989	—	`—`	Information filtering: Selection mechanisms in learning systems. Shaul Markovitch
1989	A*	`conf`	Learning Novel Domains Through Curiosity and Conjecture. IJCAI Paul D. Scott, Shaul Markovitch
1989	—	`conf`	Uncertainty Based Selection of Learning Experiences. ML Paul D. Scott, Shaul Markovitch
1989	A*	`conf`	Utilization Filtering: A Method for Reducing the Inherent Harmfulness of Deductively Learned Knowledge. IJCAI Shaul Markovitch, Paul D. Scott
1988	—	`conf`	The Role of Forgetting in Learning. ML Shaul Markovitch, Paul D. Scott