Yoav Freund

Yoav Freund

Infobox_Scientist
name = Yoav Freund


image_width =
caption =
birth_date =
birth_place =
residence =
nationality =
field = Computer Science
work_institution = University of California, San Diego
alma_mater = University of California, Santa Cruz
doctoral_advisor = Manfred K. Warmuth, David Haussler
doctoral_students =
known_for = AdaBoost
prizes = Gödel prize (2003)

Yoav Freund is a researcher and professor at the University of California, San Diego who mainly works on machine learning, probability theory and related fields and applications.

From his homepage:

My main area of research is computational learning theory and the related areas in probability theory, information theory, statistics and pattern recognition. I work on applications of machine learning algorithms in bio-informatics, computer vision, network routing and high-performance computing.

He is probably best-known for his work on the AdaBoost algorithm, a meta-learning algorithm which is used to combine many "weak" learning machines to create a more robust one. He received the Gödel prize in 2003 for his work on AdaBoost with Robert Schapire.

Professor Freund is a Talpiot program graduate.

External links

* [http://www.cs.ucsd.edu/~yfreund/ Freund's homepage at UCSD]

ee also

*AdaBoost


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  • Freund (Familienname) — Freund ist ein Familienname. Bekannte Namensträger Inhaltsverzeichnis A B C D E F G H I J K L M N O P Q R S T U V W X Y Z …   Deutsch Wikipedia

  • Prix Gödel — Nommé en l honneur du logicien Kurt Gödel, le prix Gödel a été créé en 1992 par l European Association for Theoretical Computer Science (EATCS), l Association for Computing Machinery (ACM) et le groupe de l ACM sur l algorithmique et la théorie… …   Wikipédia en Français

  • AdaBoost — (сокращение от Adaptive Boosting)  алгоритм машинного обучения, предложенный Йоавом Фройндом (en:Yoav Freund) и Робертом Шапирe (en:Robert Schapire). Этот алгоритм может использоваться в сочетании со многими другими алгоритмами обучения для… …   Википедия

  • Boosting — is a machine learning meta algorithm for performing supervised learning. Boosting is based on the question posed by KearnsMichael Kearns. Thoughts on hypothesis boosting. Unpublished manuscript. 1988] : can a set of weak learners create a single… …   Wikipedia

  • BrownBoost — BrownBoost  алгоритм бустинга, который показал свою эффективность на зашумленных наборах данных. Как и все алгоритмы бустинга, BrownBoost используется в сочетании с другими алгоритмами машинного обучения. Алгоритм BrownBoost был предложен… …   Википедия

  • AdaBoost — AdaBoost, short for Adaptive Boosting, is a machine learning algorithm, formulated by Yoav Freund and Robert Schapire. It is a meta algorithm, and can be used in conjunction with many other learning algorithms to improve their performance.… …   Wikipedia

  • BrownBoost — is a boosting algorithm that may be robust to noisy datasets. BrownBoost is an adaptive version of the boost by majority algorithm. As is true for all boosting algorithms, BrownBoost is used in conjunction with other machine learning methods.… …   Wikipedia

  • AdaBoost — (ou adaptive boosting) est une méthode de boosting (intelligence artificielle, apprentissage automatique) introduite par Yoav Freund et Robert Schapire. Ce fut l une des premières méthodes pleinement fonctionnelles permettant de mettre en œuvre… …   Wikipédia en Français

  • Alternating decision tree — An Alternating Decision Tree (ADTree) is a machine learning methodfor classification. The ADTree data structure and algorithmare a generalization of decision trees and have connections to boosting. ADTrees were introduced by Yoav Freund and Llew… …   Wikipedia

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