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Chih-Jen Lin

Showing results (1-10 of 56) with videos related to

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IEEE Transactions on Neural Networks|February 5, 2008
A formal analysis of stopping criteria of decomposition methods for support vector machinesChih-Jen Lin
IEEE Transactions on Neural Networks|February 5, 2008
Errata to "On the convergence of the decomposition method for support vector machines"Chih-Jen Lin
Neural Computation|August 25, 2007
Projected gradient methods for nonnegative matrix factorizationChih-Jen Lin
IEEE Transactions on Neural Networks|February 5, 2008
Asymptotic convergence of an SMO algorithm without any assumptionsChih-Jen Lin
IEEE Transactions on Neural Networks and Learning Systems|May 8, 2024
One-Class SVM Probabilistic OutputsZhongyi Que, Chih-Jen Lin
Reproduction (Cambridge, England)|September 8, 2016
Epigenetic reprogramming of the zygote in mice and men: on your marks, get set, go!Rupsha Fraser, Chih-Jen Lin
IEEE Transactions on Neural Networks and Learning Systems|January 11, 2021
A Study on Truncated Newton Methods for Linear ClassificationLeonardo Galli, Chih-Jen Lin
IEEE Transactions on Neural Networks and Learning Systems|February 20, 2020
Parameter Selection for Linear Support Vector RegressionJui-Yang Hsia, Chih-Jen Lin
IEEE Transactions on Neural Networks|February 5, 2008
A study on reduced support vector machinesKuan-Ming Lin, Chih-Jen Lin
Neural Computation|August 16, 2002
Training nu-support vector regression: theory and algorithmsChih-Chung Chang, Chih-Jen Lin
Pageof 6

Showing results (1-10 of 56) with videos related to

Sort By:
Pageof 6
IEEE Transactions on Neural Networks|February 5, 2008
A formal analysis of stopping criteria of decomposition methods for support vector machinesChih-Jen Lin
IEEE Transactions on Neural Networks|February 5, 2008
Errata to "On the convergence of the decomposition method for support vector machines"Chih-Jen Lin
Neural Computation|August 25, 2007
Projected gradient methods for nonnegative matrix factorizationChih-Jen Lin
IEEE Transactions on Neural Networks|February 5, 2008
Asymptotic convergence of an SMO algorithm without any assumptionsChih-Jen Lin
IEEE Transactions on Neural Networks and Learning Systems|May 8, 2024
One-Class SVM Probabilistic OutputsZhongyi Que, Chih-Jen Lin
Reproduction (Cambridge, England)|September 8, 2016
Epigenetic reprogramming of the zygote in mice and men: on your marks, get set, go!Rupsha Fraser, Chih-Jen Lin
IEEE Transactions on Neural Networks and Learning Systems|January 11, 2021
A Study on Truncated Newton Methods for Linear ClassificationLeonardo Galli, Chih-Jen Lin
IEEE Transactions on Neural Networks and Learning Systems|February 20, 2020
Parameter Selection for Linear Support Vector RegressionJui-Yang Hsia, Chih-Jen Lin
IEEE Transactions on Neural Networks|February 5, 2008
A study on reduced support vector machinesKuan-Ming Lin, Chih-Jen Lin
Neural Computation|August 16, 2002
Training nu-support vector regression: theory and algorithmsChih-Chung Chang, Chih-Jen Lin
Pageof 6