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ORCIDAmir Navot
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2000 – 2009
- 2006
[b1]Amir Navot:
On the role of feature selection in machine learning (על בחירת תכוניות בלמידה חישובית.). Hebrew University of Jerusalem, Israel, 2006- [p2]Ran Gilad-Bachrach
, Amir Navot:
Margin Based Feature Selection and Infogain with Standard Classifiers. Feature Extraction 2006: 395-401 - [p1]Ran Gilad-Bachrach, Amir Navot, Naftali Tishby:
Large Margin Principles for Feature Selection. Feature Extraction 2006: 585-606 - 2005
- [c7]Ran Gilad-Bachrach, Amir Navot, Naftali Tishby:
Query by Committee Made Real. NIPS 2005: 443-450 - [c6]Amir Navot, Lavi Shpigelman, Naftali Tishby, Eilon Vaadia:
Nearest Neighbor Based Feature Selection for Regression and its Application to Neural Activity. NIPS 2005: 996-1002 - [c5]Amir Navot, Ran Gilad-Bachrach, Yiftah Navot, Naftali Tishby:
Is Feature Selection Still Necessary? SLSFS 2005: 127-138 - 2004
- [c4]Ran Gilad-Bachrach, Amir Navot, Naftali Tishby:
Bayes and Tukey Meet at the Center Point. COLT 2004: 549-563 - [c3]Ran Gilad-Bachrach, Amir Navot, Naftali Tishby:
Margin based feature selection - theory and algorithms. ICML 2004 - 2003
- [c2]Ran Gilad-Bachrach, Amir Navot, Naftali Tishby:
An Information Theoretic Tradeoff between Complexity and Accuracy. COLT 2003: 595-609 - 2002
- [c1]Koby Crammer, Ran Gilad-Bachrach, Amir Navot, Naftali Tishby:
Margin Analysis of the LVQ Algorithm. NIPS 2002: 462-469
Coauthor Index
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