Shaul Markovitch
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Shaul Markovitch [1]
Shaul Markovitch,
an Israeli computer scientist, AI researcher, and faculty member in the Computer Science department at Technion - Israel Institute of Technology.
His research covers machine learning and AI with the topics selective learning, speedup learning,
feature generation, active learning, learning in multi-agent systems, opponent modeling, game playing, anytime algorithms, resource-bounded reasoning, reasoning under uncertainty, and heuristic search
[2].
Contents
Photos
Shaul Markovitch talks on How Computers Play Chess at the Man vs Machine Symposium, University of Haifa, October 2002 [3]
Selected Publications
1990 ...
- Shaul Markovitch, Yaron Sella (1993). Learning of Resource Allocation Strategies for Game Playing. IJCAI 1993, pdf
- David Carmel, Shaul Markovitch (1993). Learning Models of Opponent's Strategy in Game Playing. AAAI 1993, FS-93-02, pdf
- David Carmel, Shaul Markovitch (1994). The M* Algorithm: Incorporating Opponent Models into Adversary Search. CIS Report #9402, pdf [5]
- David Carmel, Shaul Markovitch (1995). Opponent Modeling in Multi-Agent Systems. IJCAI 1995, pdf
- David Carmel, Shaul Markovitch (1996). Incorporating Opponent Models into Adversary Search. AAAI 1996, pdf
- David Carmel, Shaul Markovitch (1997). Exploration and Adaptation in Multiagent Systems: A Model-based Approach. IJCAI 1997, pdf
- David Carmel, Shaul Markovitch (1998). How to Explore your Opponent's Strategy (almost) Optimally. ICMAS 1998
- Lev Finkelstein, Shaul Markovitch (1998). Learning to Play Chess Selectively by Acquiring Move Patterns. ICCA Journal, Vol. 21, No. 2, pdf
- Lev Finkelstein, Shaul Markovitch (1998). A Selective Macro-learning Algorithm and its Application to the NxN Sliding-Tile Puzzle. JAIR, Vol. 8, arXiv:cs/9806102
- David Carmel, Shaul Markovitch (1998). Pruning Algorithms for Multi-Model Adversary Search. Artificial Intelligence, Vol. 99, No. 2
2000 ...
- Shaul Markovitch (2002). Tutorial: How Computers Play Chess. Man vs Machine Symposium
- Lev Finkelstein, Shaul Markovitch, Ehud Rivlin (2003). Optimal Schedules for Parallelizing Anytime Algorithms: The Case of Shared Resources. JAIR, Vol. 19, arXiv:1106.5269
- Dmitry Davidov, Shaul Markovitch (2006). Multiple-Goal Heuristic Search. JAIR, Vol. 26, arXiv:1109.6618
- Evgeniy Gabrilovich, Shaul Markovitch (2007). Computing Semantic Relatedness Using Wikipedia-based Explicit Semantic Analysis. IJCAI 2007, pdf
- Saher Esmeir, Shaul Markovitch (2007). Occam's Razor Just Got Sharper. IJCAI 2007, pdf
- Evgeniy Gabrilovich, Shaul Markovitch (2009). Wikipedia-based Semantic Interpretation for Natural Language Processing. JAIR, Vol. 34, arXiv:1401.5697
2010 ...
- Carmel Domshlak, Erez Karpas, Shaul Markovitch (2012). Online Speedup Learning for Optimal Planning. JAIR, Vol. 44, arXiv:1401.5861
- Lior Friedman, Shaul Markovitch (2018). Recursive Feature Generation for Knowledge-based Learning. arXiv:1802.00050
2020 ...
- Michal Badian, Shaul Markovitch (2020). Knowledge-Based Learning through Feature Generation. arXiv:2006.03874
External Links
- Shaul Markovitch's Home Page
- Shaul Markovitch - Google Scholar Citations
- Shaul Markovitch - YouTube
- Shaul Markovitch, Ziv Cohen, Peer Sagiv, Ilya Smagloy - Shine On You Crazy Diamond, Technion, November 04, 2019, YouTube Video
References
- ↑ Shaul Markovitch's Home Page
- ↑ Shaul Markovitch - Research summary
- ↑ Man vs. Machine: The Experiment October 15-16, 2002, University of Haifa
- ↑ dblp: Shaul Markovitch
- ↑ Re: Different eval for white/black by Ronald de Man, CCC, January 08, 2015
