Zobrazeno 1 - 10
of 95
pro vyhledávání: '"Vapnik, Vladimir"'
Autor:
Vapnik, Vladimir, Izmailov, Rauf
Publikováno v:
In Pattern Recognition November 2021 119
Publikováno v:
Proceedings of the International Conference on Learning Representations (2016) 1-10
Distillation (Hinton et al., 2015) and privileged information (Vapnik & Izmailov, 2015) are two techniques that enable machines to learn from other machines. This paper unifies these two techniques into generalized distillation, a framework to learn
Externí odkaz:
http://arxiv.org/abs/1511.03643
Autor:
Mukherjee, Sayan, Vapnik, Vladimir
We formulate density estimation as an inverse operator problem. We then use convergence results of empirical distribution functions to true distribution functions to develop an algorithm for multivariate density estimation. The algorithm is based upo
Externí odkaz:
http://hdl.handle.net/1721.1/7260
We introduce a general constructive setting of the density ratio estimation problem as a solution of a (multidimensional) integral equation. In this equation, not only its right hand side is known approximately, but also the integral operator is defi
Externí odkaz:
http://arxiv.org/abs/1306.0407
We describe a method for predicting a classification of an object given classifications of the objects in the training set, assuming that the pairs object/classification are generated by an i.i.d. process from a continuous probability distribution. O
Externí odkaz:
http://arxiv.org/abs/1301.7375
Publikováno v:
Journal for General Philosophy of Science / Zeitschrift für allgemeine Wissenschaftstheorie, 2009 Jul 01. 40(1), 51-58.
Externí odkaz:
https://www.jstor.org/stable/40390670
Autor:
Nouretdinov, Ilia, Costafreda, Sergi G., Gammerman, Alexander, Chervonenkis, Alexey, Vovk, Vladimir, Vapnik, Vladimir, Fu, Cynthia H.Y.
Publikováno v:
In NeuroImage 15 May 2011 56(2):809-813
Autor:
Vapnik, Vladimir, Vashist, Akshay
Publikováno v:
In Neural Networks 2009 22(5):544-557
Publikováno v:
Statistical Analysis & Data Mining. Jun2015, Vol. 8 Issue 3, p137-146. 10p.