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Topic: Vladimir Vapnik

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Vapnik Chervonenkis theory

	Vladimir Vapnik - Wikipedia, the free encyclopedia
		Vladimir Naumovich Vapnik is one of the main developers of Vapnik Chervonenkis theory.
		He was born in Soviet Union; received a master's degree in mathematics from the Uzbek State University in Samarkand (now Uzbekistan), in 1958; and received a Ph.D in statistics from the Institute of Control Science in Moscow in 1964.
		At ATandT Bell Labs (later Shannon Labs) from 1991 through 2001?, Vapnik and his colleagues developed the theory of the support vector machine.
	en.wikipedia.org /wiki/Vladimir_Vapnik (214 words)

	vladimir vapnik (Site not responding. Last check: 2007-11-07)
		Vladimir Naumovich Vapnik is one of the main developers of statistical learning theory.
		He was born in Russia; received a master's degree in mathematics from the Uzbek State University in Samarkand, in 1958; and received a Ph.D in statistics from the Institute of Control Science in Moscow, in 1964.
		At AT&T; Bell Labs (later Shannon Labs) from 1991 through 2001?, Vapnik and his colleagues developed the theory of the support vector machine.
	www.yourencyclopedia.net /vladimir_vapnik.html (168 words)

	PRESS RELEASE Humboldt Research Award Winner Professor Dr. Vladimir Vapnik, Named to Health Discovery Corporation ... (Site not responding. Last check: 2007-11-07)
		Vapnik is the 2003 winner of the Humboldt Research Award.
		Vapnik said, "We are on the cusp of major breakthroughs in creating medical treatments personalized for individual patients.
		Professor Vapnik's major achievements include the development of a general theory for minimizing the expected risk of losses using empirical data and a new type of learning machine that possesses a high level of generalization ability.
	www.marketwire.com /mw/release_html_b1?release_id=69854 (586 words)

	Vladimir Vapnik
		Vladimir Vapnik is one of the main developers of Statistical Learning Theory[?].
		At AT&T Bell (later Shannon) Labs from 1991 through 2001?, Vapnik and his colleagues developed the theory of the Support Vector Machine.
		The text of this article is licensed under the GFDL.
	www.ebroadcast.com.au /lookup/encyclopedia/vl/Vladimir_Vapnik.html (123 words)

	KXEN - Professor Vladimir Vapnik, Humboldt Research Award winner, joins KXEN’s scientific committee
		Professor Vapnik is an international expert on Machine Learning and theoretical and applied statistics, and is a widely published author on these topics.
		Professor Vapnik’s major achievements include the development of a general theory for minimizing the expected risk of losses using empirical data, and a new type of learning machine called the Support Vector machine that possesses a high level of generalization ability.
		Vapnik has taught and researched in theoretical and applied statistics for over 30 years.
	www.kxen.com /news/2003_04_14.html (492 words)

	Support Vector Machines - The Book
		Support Vector Machines are a very specific class of algorithms, characterised by the use of kernels, the absence of local minima, the sparseness of the solution and the capacity control obtained by acting on the margin, or on other `dimension independent' quantities such as the number of support vectors.
		Cortes and Vapnik, and in 1995 the algorithm was extended to the regression case.
		Opper and Winther, which provide a cross-validation analysis of the expected error, and the book Vapnik, which gives an expected error bound in terms of the margin and radius of the smallest ball containing the essential support vectors.
	www.support-vector.net /chapter_6.html (923 words)

	Vladimir Vapnik (Site not responding. Last check: 2007-11-07)
		At ATandT Bell Labs (later Shannon Labs) from 1991 through Vapnik and his colleagues developed the theory the support vector machine.
		They demonstrated its performance on a of problems of interest to the machine learning community including handwriting recognition.
		When pianists become as good at Beethoven as Vladimir Ashkenazy or Alfred Brendel it comes down to opinon of which you enjoy the most.
	www.freeglossary.com /Vladimir_Vapnik (482 words)

	El Profesor del Ganador del Premio de Investigaciónde Humboldt Dr. Vladimir Vapnik, Denominado a la Corporación del ... (Site not responding. Last check: 2007-11-07)
		Vapnik proporciona nos da una pala muy rápida, muy precisa y muy grande.
		Vapnik dijo, "estamos en la cúspide de adelantos mayores a crear los tratamientos médicos personalizados para pacientes individuales.
		Vapnik de profesor los logros mayores incluyen el desarrollo de una teoría general para aminorar el riesgo esperado de las pérdidas que utilizan los datos empíricos y un tipo nuevo de aprender máquina que posee un nivel alto de la habilidad de generalización.
	espanol.empirerelations.com /news/hdvy/h071304.shtml (822 words)

	Vapnik Chervonenkis theory - Wikipedia, the free encyclopedia
		Vapnik Chervonenkis theory (also known as VC theory) was developed during 1960-1990 by Vladimir Vapnik and Alexey Chervonenkis.
		The theory is a form of computational learning theory, which attempts to explains the learning process from a statistical point of view.
		The Nature of Statistical Learning Theory, Vladimir Vapnik, Springer-Verlag, (1999), ISBN 0387987800
	en.wikipedia.org /wiki/Vapnik_Chervonenkis_theory (238 words)

	Computergram International: Norkom Looks for Gold with Alchemist CRM
		One of these, the Vladimir Vapnik technique, developed by a Russian mathematician employed by Bell Labs, has been taken on an OEM basis from KXEN, a French developer of military and meteorological analysis systems, and adapted to the needs of Norkom's target markets, which include the retail finance, insurance and telecommunications sectors.
		However Vapnik "introduces noise" to the sample data, making the training exercise more realistic, and increasing the likelihood that the same levels of accuracy will be carried over from the sample exercise to the full database implementation.
		The ease of use of Vapnik should also make it simpler to put directly into the hands of the end-users, says Kerley, and Alchemist is configured as a thin-client system that will give users direct access to their analytic algorithms via a web portal.
	www.findarticles.com /p/articles/mi_m0CGN/is_3690/ai_54997674 (766 words)

	Buecher Kaufempfehlung: The Nature of Statistical Learning Theory von Vladimir N. Vapnik bei Springer-Verlag New York ... (Site not responding. Last check: 2007-11-07)
		The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization.
		Vladimir N. Vapnik is Technology Leader AT&T Labs-Research and Professor of London University.
		Vapnik and collaborators have developed the field of statistical learning theory underlying recent advances in machine learning and artificial intelligence (e.g.
	www.buchlisten.schnellsuchmaschine.de /0387987800-The_Nature_of_Statistical_Learning_Theory_von_Vladimir_N_Vapnik_bei_Springer_Verlag_New_York_Inc_.html (439 words)

	Statistical Learning Theory by Vladimir N. Vapnik (Site not responding. Last check: 2007-11-07)
		Comment: Vapnik and Chernovenkis extended the Glivenko-Cantelli Theorem in their work on classification and statistical learning.
		Vapnik in recent texts has described a form of nonparametric statistical inference based on approximating functions and the Vapnik-Chernovenkis dimension.
		However Vapnik sees a much broader application to statistical inference in general when the classical parametric approach fails.
	www.internetcross.com /item/0471030031 (1158 words)

	With the NATO in Leuven (Site not responding. Last check: 2007-11-07)
		This place has two other claims to fame: the Germans used it in WWII as their local HQ, and I had courses there around 1970 as an undergraduate student.
		Vladimir Vapnik, the father of the Vapnik-Chervonenkis theory and the support vector machines.
		Vapnik with Nello and the main organizer, Johan Suykens.
	cgm.cs.mcgill.ca /~luc/lunch02-jul8.html (136 words)

	Statistical learning theory - Wikipedia, the free encyclopedia
		It may refer to computational learning theory, which is a sub-field of statistics that studies how algorithms can learn from data.
		It may refer to Vapnik Chervonenkis theory, which is a specific approach to computational learning theory, proposed by Vladimir Vapnik and Alexey Chervonenkis.
		This is a disambiguation page, a list of pages that otherwise might share the same title.
	en.wikipedia.org /wiki/Statistical_learning_theory (117 words)

	Vladimir Nabokov
		The eldest son of Vladimir Dmitrievich Nabokov and his wife Elena, née Elena Ivanovna Rukavishnikova, he was born in St. Petersburg where he also spent his childhood and youth.After emigration from Russia in 1919, the family settled briefly in England and Vladimir enrolled in Cambridge for his studies of French and Russian literature.
		Vladimir Dmitrievich Nabokov (July 15, 1870 - March 28, 1922) was a Russian criminologist, publisher and liberal politician.He was born in Tsarskoe Selo.
		Their eldest son was Vladimir Vladimirovich Nabokov, who portrayed his father in his memoirs (Speak, Memory, 1967).
	isbnlookup.com /964812_vladimir-nabokov_0297179357adacollegetextbooksused.html (914 words)

	DBLP: Olivier Chapelle
		Jason Weston, Olivier Chapelle, André Elisseeff, Bernhard Schölkopf, Vladimir Vapnik: Kernel Dependency Estimation.
		Vladimir Vapnik, Olivier Chapelle: Bounds on Error Expectation for Support Vector Machines.
		Olivier Chapelle, Vladimir Vapnik, Jason Weston: Transductive Inference for Estimating Values of Functions.
	informatik.uni-trier.de /~ley/db/indices/a-tree/c/Chapelle:Olivier.html (241 words)

	DBLP: Vladimir Vapnik
		Vladimir Vapnik, Steven E. Golowich, Alex J. Smola: Support Vector Method for Function Approximation, Regression Estimation and Signal Processing.
		Corinna Cortes, Harris Drucker, Dennis Hoover, Vladimir Vapnik: Capacity and Complexity Control in Predicting the Spread Between Borrowing and Lending Interest Rates.
		Vladimir Vapnik: Inductive Principles of the Search for Empirical Dependences (Methods Based on Weak Convergence of Probability Measures).
	dblp.uni-trier.de /db/indices/a-tree/v/Vapnik:Vladimir.html (546 words)

	Vladimir Vapnik Encyclopedia Article, Definition, History, Biography (Site not responding. Last check: 2007-11-07)
		Looking For vladimir vapnik - Find vladimir vapnik and more at Lycos Search.
		Find vladimir vapnik - Your relevant result is a click away!
		Look for vladimir vapnik - Find vladimir vapnik at one of the best sites the Internet has to offer!
	www.karr.net /search/encyclopedia/Vladimir_Vapnik (382 words)

	[Cnrc-seminars] [Colloquium] Vladimir Vapnik, AT&T Labs (Site not responding. Last check: 2007-11-07)
		The problems of induction, statistical analysis and computer learning Vladimir Vapnik ATandT Labs Columbia Lectures in Computer Science Monday, December 17, 2001 11:00 a.m.
		Biography: Vladimir Vapnik gained his PhD Degree in Mathematics.
		I will try to show how the machine learning paradigm overcomes the "curse of dimensionality".andnbsp; In particular I will consider Support Vector Machines, discuss their connections to the general theory of inference, and demonstrate their advantage in solving high-dimensional real-life problems.
	lists.cs.columbia.edu /pipermail/cnrc-seminars/2001/000038.html (545 words)

	RHUL Computer Science: Events (Site not responding. Last check: 2007-11-07)
		In particular, there was discussion on how to find the best, in the MDL sense, wavelet basis for data, as well as how to smoothen a data sequence by removing the MDL-defined noise from it.
		At the same time, in the 1960's, Vladimir Vapnik and Alexei Chervonenkis started the development of another induction principle - what is now known as Structured Risk Minimalization (SRM) principle.
		I strongly believe that today's colloquium will be remembered as a very important step in the development of modern induction theory, and the theory of learning.
	www.cs.rhul.ac.uk /events/compintday.shtml (1244 words)

	IBM Haifa Labs \| News Center
		A highlight of the seminar was the keynote address delivered by Vladimir Vapnik, one of the founding fathers of the machine learning field.
		Considered by many to be the most important figure in this area, Vapnik reviewed the main innovations and breakthroughs of machine learning since the early 60's, highlighting new trends and technologies developed in the last decade.
		Currently at NEC Laboratories and Columbia University, Vapnik believes the field is moving from an era of deductive reasoning, in which data was used to build models for predicting further data, to an era of transductive reasoning.
	www.research.ibm.com /haifa/info/news_ibm_ml2005.html (433 words)

	Vladimir Vapnik - Encyclopedia, History, Geography and Biography (Site not responding. Last check: 2007-11-07)
		Vladimir Vapnik - Encyclopedia, History, Geography and Biography
		This page was last modified 19:42, 9 Jun 2005.
		The article about Vladimir Vapnik contains information related to Vladimir Vapnik and External links.
	www.arikah.com /encyclopedia/Vladimir_Vapnik (194 words)

	Professor Vapnik
		Professor Vapnik gained his Masters Degree in Mathematics in 1958 at Uzbek State University, Samarkand, USSR.
		From 1961 to 1990 he worked at the Institute of Control Sciences, Moscow, where he became Head of the Computer Science Research Department.
		Professor Vapnik has taught and researched in computer science, theoretical and applied statistics for over 30 years.
	www.clrc.rhul.ac.uk /people/vlad (208 words)

	Tutorials at NIPS 1997
		In the tutorial examples of solving various pattern recognition and regression estimation problems will be given and the results obtained will be compared with the results obtained using existing state-of-the-art techniques including neural networks.
		Vladimir Vapnik, currently Member of Technical Staff, AT&T Labs-Research, is one of the creators of the theory of learning and generalization, the so-called VC theory (abbreviation for the Vapnik-Chervonenkis theory).
		Vladimir Vapnik is the author of 7 monographs and more than 100 articles devoted to various problems of statistics and problems of learning and generalization.
	www.cs.cmu.edu /Groups/NIPS/1997/Tutorials.html (1631 words)

	DBLP: Vladimir Vapnik
		Vladimir Vapnik, Sayan Mukherjee: Support Vector Method for Multivariate Density Estimation.
		Bernhard E. Boser, Isabelle Guyon, Vladimir Vapnik: A Training Algorithm for Optimal Margin Classifiers.
		Isabelle Guyon, Vladimir Vapnik, Bernhard E. Boser, Léon Bottou, Sara A. Solla: Structural Risk Minimization for Character Recognition.
	www.informatik.uni-trier.de /~ley/db/indices/a-tree/v/Vapnik:Vladimir.html (546 words)

	KXEN - Scientific Board
		He spent twelve months in Bell Labs where he met Vladimir Vapnik and made several contributions to Vapnik’s statistical learning theory.
		Olivier Chapelle graduated from the Ecole Normale Superieure de Lyon in 1999 and is currently pursuing a PhD at the University of Paris 6 in the field of learning theory with advisors Vladimir Vapnik and Patrick Gallinari.
		Professor Vapnik, one of the fathers of Statistical Learning Theory, received his Masters Degree in Mathematics in 1958 at Uzbek State University, Samarkand, USSR.
	www.kxen.com /about/scientific_board.php (1301 words)

	[No title]
		The author of this theory, famous Russian scientist Vladimir Vapnik, whom working now in AT&T Research Lab, sum up several his old ideas and invented this, so popular today, approach.
		Vapnik noticed some interesting features of the dual task.
		That is why Vapnik decided do not use criterion (5) for non-separable case.
	www.cs.rutgers.edu /pub/seredin/LinearSVApproach.doc (1375 words)

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