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Wednesday, 20 February 2008 William H. Hsu Department of Computing and Information Sciences, KSU

Wednesday, 20 February 2008 William H. Hsu Department of Computing and Information Sciences, KSU

Lecture 13 of 42. Support Vector Machines (concluded) and Association Rule Mining. Wednesday, 20 February 2008 William H. Hsu Department of Computing and Information Sciences, KSU http://www.kddresearch.org/Courses/Spring-2008/CIS732/ Readings:

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767 views • 65 slides
A Simple Introduction to Support Vector Machines

A Simple Introduction to Support Vector Machines

A Simple Introduction to Support Vector Machines. Martin Law Lecture for CSE 802 Department of Computer Science and Engineering Michigan State University. Outline. A brief history of SVM Large-margin linear classifier Linear separable Nonlinear separable

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771 views • 48 slides
A Simple Introduction to Support Vector Machines

A Simple Introduction to Support Vector Machines

A Simple Introduction to Support Vector Machines. Martin Law Lecture for CSE 802 Department of Computer Science and Engineering Michigan State University. Outline. A brief history of SVM Large-margin linear classifier Linear separable Nonlinear separable

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706 views • 48 slides
Wireless Coexistence in Open Radio Spectrum: Curses and Blessings

Wireless Coexistence in Open Radio Spectrum: Curses and Blessings

Wireless Coexistence in Open Radio Spectrum: Curses and Blessings. Guoliang Xing Assistant Professor Department of Computer Science and Engineering Michigan State University. Outline. Wireless Coexistence in Open Radio Spectrum ZigBee link quality assurance [ICNP10, best paper award ]

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721 views • 45 slides
Collaborative Filtering

Collaborative Filtering

Collaborative Filtering. Rong Jin Department of Computer Science and Engineering Michigan State University. Outline. Brief introduction information filtering Collaborative filtering Major issues in collaborative filtering Main methods for collaborative filtering

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677 views • 33 slides
An Introduction to the Expectation-Maximization (EM) Algorithm

An Introduction to the Expectation-Maximization (EM) Algorithm

An Introduction to the Expectation-Maximization (EM) Algorithm. CSE 802, Spring 2006 Department of Computer Science and Engineering Michigan State University. Overview. The problem of missing data A mixture of Gaussian The EM Algorithm The Q-function, the E-step and the M-step

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1.4k views • 22 slides
DBLA: Distributed Block Learning Algorithm For Channel Selection In Cognitive Radio Networks

DBLA: Distributed Block Learning Algorithm For Channel Selection In Cognitive Radio Networks

DBLA: Distributed Block Learning Algorithm For Channel Selection In Cognitive Radio Networks. Chowdhury Sayeed Hyder Department of Computer Science & Engineering Michigan State University. - Chowdhury Sayeed Hyder , and Li Xiao. Outline. Background Cognitive Radio Network

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292 views • 21 slides

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