Vladimir Vapnik is affiliated with Princeton University in the United States and has contributed to the field of Computer Science, particularly through work in Artificial Intelligence and Computer Vision and Pattern Recognition. Their research spans several main topics including Neural Networks and Applications, Face and Expression Recognition, and Machine Learning and Extreme Learning Machines (ELM).
Their recent publication includes a paper titled "Reinforced SVM method and memorization mechanisms" published in 2021 in the journal Pattern Recognition. This work has been cited 61 times. Pattern Recognition is also the primary venue for their publications.
Vladimir Vapnik's career includes recognition through several awards. These include the BBVA Foundation Frontiers of Knowledge Award in 2019 and the IEEE John von Neumann Medal in 2017, awarded for the development of statistical learning theory, theoretical foundations for machine learning, and support vector machines.
Other honors include the Benjamin Franklin Medal from the Franklin Institute and the IEEE Frank Rosenblatt Award, both received in 2012, the Neural Networks Pioneer Award from the IEEE Computational Intelligence Society in 2010, and the ACM Paris Kanellakis Theory and Practice Award in 2008 for the development of Support Vector Machines.
Vapnik was also inducted as a Member of the National Academy of Engineering in 2006 for insights into the fundamental complexities of learning and inventing practical machine-learning algorithms.
Vladimir N. Vapnik
Vladimir Naumovich Vapnik
Corinna Cortes;Vladimir Vapnik
Unknown
Bernhard E. Boser;Isabelle M. Guyon;Vladimir N. Vapnik
Isabelle Guyon;Jason Weston;Stephen Barnhill;Vladimir Vapnik
Vladimir Vapnik;A. Ya. Chervonenkis
Harris Drucker;Christopher J. C. Burges;Linda Kaufman;Alex J. Smola
V.N. Vapnik
Vladimir Naumovich Vapnik
Vladimir Vapnik;Steven E. Golowich;Alex J. Smola
V. N. Vapnik
Olivier Chapelle;Vladimir Vapnik;Olivier Bousquet;Sayan Mukherjee
Vladimir Vapnik;Sayan Mukherjee
O. Chapelle;P. Haffner;V.N. Vapnik
H. Drucker;Donghui Wu;V.N. Vapnik
Asa Ben-Hur;David Horn;Hava T. Siegelmann;Vladimir Vapnik
B. Scholkopf;Kah-Kay Sung;C.J.C. Burges;F. Girosi
V. Vapnik
Jason Weston;Sayan Mukherjee;Olivier Chapelle;Massimiliano Pontil
Klaus-Robert Müller;Alex J. Smola;Gunnar Rätsch;Bernhard Schölkopf
If you think any of the details on this page are incorrect, let us know.
Exploring computer science in the USA opens doors to a wide range of academic and professional options. Many students now choose online degrees for their flexibility and accessibility. For those seeking a quick entry into the tech workforce, online associate degree programs can provide essential skills within just a few months.
The field of computer science also closely connects with business and engineering. If you're looking to blend tech knowledge with managerial expertise, consider reputable online business degree programs. Similarly, students aspiring to integrate engineering concepts into their tech careers can explore diverse online engineering degrees.
Financial concerns are common among international and domestic students alike. To help ease tuition costs, you can research affordable online colleges that offer quality computer science courses and broader degree options. Whether you are starting your education or considering a career switch, these pathways can launch you into thriving industries with strong job prospects.
University of Göttingen
University of Iceland
University of Hohenheim
University of New South Wales
Johns Hopkins University
Chiang Mai University
Vrije Universiteit Amsterdam
Nathan Kline Institute for Psychiatric Research
University of Lausanne
Commonwealth Scientific and Industrial Research Organisation
University of Hawaii at Manoa
Johns Hopkins University School of Medicine
Royal Orthopaedic Hospital
University of North Carolina at Chapel Hill
Pontificia Universidad Católica de Chile
University of Georgia
