Amir Navot
Amir Navot
Principal Research Scientist at Amazon Prime Air
Verified email at
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Margin based feature selection-theory and algorithms
R Gilad-Bachrach, A Navot, N Tishby
Proceedings of the twenty-first international conference on Machine learning, 43, 2004
Margin analysis of the LVQ algorithm
K Crammer, R Gilad-Bachrach, A Navot, N Tishby
NIPS 2, 462-469, 2002
Nearest neighbor based feature selection for regression and its application to neural activity
A Navot, L Shpigelman, N Tishby, E Vaadia
Advances in neural information processing systems 18, 995, 2006
Query by committee made real
R Gilad-Bachrach, A Navot, N Tishby
NIPS 5, 443-450, 2005
An information theoretic tradeoff between complexity and accuracy
R Gilad-Bachrach, A Navot, N Tishby
Learning Theory and Kernel Machines, 595-609, 2003
Learning to Select Features using their Properties.
E Krupka, A Navot, N Tishby
Journal of Machine Learning Research 9 (10), 2008
On the role of feature selection in machine learning
A Navot
Hebrew University, 2006
Is feature selection still necessary?
A Navot, R Gilad-Bachrach, Y Navot, N Tishby
International Statistical and Optimization Perspectives Workshop" Subspace …, 2005
Large margin principles for feature selection
R Gilad-Bachrach, A Navot, N Tishby
Feature Extraction, 585-606, 2006
Kernel query by committee (KQBC)
R Gilad-Bachrach, A Navot, N Tishby
Leibniz Center, Hebrew Univ., Jerusalem, Israel, Tech. Rep 88, 2004, 2003
Bayes and tukey meet at the center point
R Gilad-Bachrach, A Navot, N Tishby
International Conference on Computational Learning Theory, 549-563, 2004
Sea Spotter: A fully staring Naval IRST System
NS Michael Engel, Amir Navot, Izhak Saban, Yaakov Engel, Eyal Arad
Proc SPIE, 2013
Margin Based Feature Selection and Infogain with Standard Classifiers
R Gilad-Bachrach, A Navot
Feature Extraction, 395-401, 2006
Bayes and Tukey Meet at the Center Point Ran Gilad-Bachrach
A Navot
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