18.465 Topics in Statistics: Statistical Learning Theory, Spring 2004

18.465 Topics in Statistics: Statistical Learning Theory, Spring 2004

The main goal of this course is to study the generalization ability of a number of popular machine learning algorithms such as boosting, support vector machines and neural networks. Topics include Vapnik-Chervonenkis theory, concentration inequalities in product spaces, and other elements of empiric...

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Xehetasun bibliografikoak
Egile nagusia: Panchenko, Dmitry A.
Beste egile batzuk: Massachusetts Institute of Technology. Department of Mathematics
Formatua: Learning Object
Hizkuntza:en-US
Argitaratua: 2004
Gaiak:
machine learning algorithms
boosting
support vector machines
neural networks
Vapnik- Chervonenkis theory
concentration inequalities in product spaces
empirical process theory
Sarrera elektronikoa:http://hdl.handle.net/1721.1/39660

Internet

http://hdl.handle.net/1721.1/39660

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