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of 2 297
pro vyhledávání: '"Vladimir Vapnik"'
Autor:
Jose Taylor, Camillo
Publikováno v:
In Journal of the Franklin Institute July 2015 352(7):2579-2584
Publikováno v:
Health & Medicine Week; 11/15/2024, p1601-1601, 1p
Akademický článek
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Autor:
Camillo J. Taylor
Publikováno v:
Journal of the Franklin Institute. 352:2579-2584
The Franklin Institute, Philadelphia, Pennsylvania, awards the 2012 Benjamin Franklin Medal in Computer and Cognitive Science to Professor Vladimir Vapnik for his fundamental contributions to our understanding of machine learning, which allows comput
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d833df532e9f5d255020e134cdf42d8d
https://doi.org/10.1016/j.jfranklin.2015.02.013
https://doi.org/10.1016/j.jfranklin.2015.02.013
Autor:
Alexey Chervonenkis
Publikováno v:
Statistical Learning and Data Science
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e22738c5fd61c7d242ebfd119a939790
https://doi.org/10.1201/b11429-7
https://doi.org/10.1201/b11429-7
Autor:
Shoesmith, E.
Publikováno v:
Journal of the Royal Statistical Society. Series D (The Statistician), 1984 Sep 01. 33(3), 324-324.
Externí odkaz:
https://www.jstor.org/stable/2988246
Autor:
Vladimir Vapnik
Publikováno v:
Automation and Remote Control. 80:1949-1975
Existing mathematical model of learning requires using training data find in a given subset of admissible function the function that minimizes the expected loss. In the paper this setting is called Second selection problem. Mathematical model of lear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b54221e7687e07565dc7ea3e6f9103bd
https://doi.org/10.1134/s000511791911002x
https://doi.org/10.1134/s000511791911002x
Autor:
Vladimir Vapnik, Rauf Izmailov
Publikováno v:
Machine Learning. 108:381-423
This paper introduces a new learning paradigm, called Learning Using Statistical Invariants (LUSI), which is different from the classical one. In a classical paradigm, the learning machine constructs a classification rule that minimizes the probabili
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2403c8c10896635fd2152f3059497313
https://doi.org/10.1007/s10994-018-5742-0
https://doi.org/10.1007/s10994-018-5742-0
Autor:
Vladimir Vapnik, Rauf Izmailov
Publikováno v:
Pattern Recognition. 119:108018
The paper is devoted to two problems: (1) reinforcement of SVM algorithms, and (2) justification of memorization mechanisms for generalization. (1) Current SVM algorithm was designed for the case when the risk for the set of nonnegative slack variabl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::34cd50618380ab9c3feaba9fb3305deb
https://doi.org/10.1016/j.patcog.2021.108018
https://doi.org/10.1016/j.patcog.2021.108018
Autor:
Rauf Izmailov, Vladimir Vapnik
Publikováno v:
Annals of Mathematics and Artificial Intelligence. 81:3-19
The paper considers general machine learning models, where knowledge transfer is positioned as the main method to improve their convergence properties. Previous research was focused on mechanisms of knowledge transfer in the context of SVM framework;
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::077fdea6c8d0e6f7eba44861940e0e9b
https://doi.org/10.1007/s10472-017-9538-x
https://doi.org/10.1007/s10472-017-9538-x