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Abstract: this article is on the theoretical side and not on the applicative one; hence, we shall not present examples which may be interesting from the practical point of view but have little theoretical significance. This survey is far from being complete and it focuses on problems the author finds interesting (an opinion which is not necessarily shared by the majority of the learning community). Relevant books which present a more evenly balanced approach are, for example [1, 4, 35, 36] The starting... (Update)
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1.3: Rademacher averages and phase transitions in Glivenko-Cantelli.. - Mendelson (2001) (Correct)
1.1: Geometric Parameters of Kernel Machines - Mendelson (Correct)
0.8: Uniform Glivenko-Cantelli Theorems and - Concentration Of Measure (2002) (Correct)
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0.4: On the Performance of Kernel Classes - Mendelson (2003) (Correct)
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3: Improving the sample complexity using global data - Mendelson - 2002
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BibTeX entry: (Update)
S. Mendelson. A few notes on statistical learning theory. In S. Mendelson and A. Smola, editors, Advanced Lectures in Machine Learning, LNCS 2600, pages 1-40. Springer, 2003. http://citeseer.ist.psu.edu/mendelson03few.html More
@misc{ mendelson03few,
author = "S. Mendelson",
title = "A few notes on statistical learning theory",
text = "S. Mendelson. A few notes on statistical learning theory. In S. Mendelson
and A. Smola, editors, Advanced Lectures in Machine Learning, LNCS 2600,
pages 1-40. Springer, 2003.",
year = "2003",
url = "citeseer.ist.psu.edu/mendelson03few.html" }
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1 Panchenko: Rademacher processes and bounding the risk of fun.. (context) - Koltchinskii - 1999
1 Oleszkiewicz: On the best constant in the Khintchine-Kahane .. (context) - Latala - 1994
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