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Advances in kernel methods: support vector learning

Advances in kernel methods: support vector learning (23회 대출)

자료유형
단행본
개인저자
Scho<lkopf, Bernhard. Burges, Christopher J. C. Smola, Alexander J.
서명 / 저자사항
Advances in kernel methods: support vector learning / edited by Bernhard Scho<lkopf, Christopher J.C. Burges, Alexander J. Smola.
발행사항
Cambridge, Mass. :   MIT Press ,   c1999.  
형태사항
vii, 376 p. : ill. ; 26 cm.
ISBN
0262194163 (alk. paper)
일반주기
Also available via the World Wide Web.
내용주기
Preface -- Introduction to support vector learning -- Roadmap -- Three remarks on the support vector method of function estimation / Valdimir Vapnik -- Generalization performance of support vector machines and other pattern classifiers / Peter Bartlett and John Shawe-Taylor -- Bayesian voting schemes and large margin classifiers / Nello Cristianini and John Shawe-Taylor -- Support vector machines, reproducing kernal Hilbert spaces, and randomized GACV / Grace Wahba -- Geometry and invariance in kernel based methods / Christopher J.C. Burgess -- On the annealed VC entropy for margin classifiers : a statistical mechanics study / Manfred Opper -- Entropy numbers, operators and support vector kernels / Robert C. Williamson, Alex J. Smola and Berhard Scho<lkopf -- Solving the quadratic programming problem arising in support vector classification / Linda Kaufman -- Making large-scale support vector machine learning practical / Thorsten Joachims -- Fast training of support vector machines using sequential minimal optimization / John C. Platt -- Support vector machines for dynamic reconstruction of a chaotic system / David Mattera and Simon Haykin -- Using support vector machines for time series prediction / Klaus-Robert Mu<ller .. [et al.] -- Pairwise classification and support vector machines / Ulrich Kressel -- Reducing the run-time complexity in support vector machines / Edgar E. Osuna and Federico Girosi -- Support vector regression with ANOVA decomposition kernels / Mark O. Stitson .. [et al.] -- Support vector density estimation / Jason Weston .. [et al.] -- Combining support vector and mathematical programming methods for classification / Kristin P. Bennett -- Kernel principal component analysis / Berhard Scho<lkopf, Alex J. Smola and Klaus-Robert Mu<ller.
서지주기
Includes bibliographical references (p. [353]-371) and index.
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Also available via the World Wide Web.  
일반주제명
Machine learning. Algorithms. Kernel functions.
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010 ▼a 98040302
015 ▼a GB99-35736
020 ▼a 0262194163 (alk. paper)
040 ▼a DLC ▼c DLC ▼d WAU ▼d UKM ▼d U6P ▼d OCL ▼d 211009
049 1 ▼l 121081571 ▼f 과학
050 0 0 ▼a Q325.5 ▼b .A32 1999
082 0 0 ▼a 006.3/1 ▼2 21
090 ▼a 006.31 ▼b A244
245 0 0 ▼a Advances in kernel methods: ▼b support vector learning / ▼c edited by Bernhard Scho<lkopf, Christopher J.C. Burges, Alexander J. Smola.
260 ▼a Cambridge, Mass. : ▼b MIT Press , ▼c c1999.
300 ▼a vii, 376 p. : ▼b ill. ; ▼c 26 cm.
504 ▼a Includes bibliographical references (p. [353]-371) and index.
505 0 ▼a Preface -- Introduction to support vector learning -- Roadmap -- Three remarks on the support vector method of function estimation / Valdimir Vapnik -- Generalization performance of support vector machines and other pattern classifiers / Peter Bartlett and John Shawe-Taylor -- Bayesian voting schemes and large margin classifiers / Nello Cristianini and John Shawe-Taylor -- Support vector machines, reproducing kernal Hilbert spaces, and randomized GACV / Grace Wahba -- Geometry and invariance in kernel based methods / Christopher J.C. Burgess -- On the annealed VC entropy for margin classifiers : a statistical mechanics study / Manfred Opper -- Entropy numbers, operators and support vector kernels / Robert C. Williamson, Alex J. Smola and Berhard Scho<lkopf -- Solving the quadratic programming problem arising in support vector classification / Linda Kaufman -- Making large-scale support vector machine learning practical / Thorsten Joachims -- Fast training of support vector machines using sequential minimal optimization / John C. Platt -- Support vector machines for dynamic reconstruction of a chaotic system / David Mattera and Simon Haykin -- Using support vector machines for time series prediction / Klaus-Robert Mu<ller .. [et al.] -- Pairwise classification and support vector machines / Ulrich Kressel -- Reducing the run-time complexity in support vector machines / Edgar E. Osuna and Federico Girosi -- Support vector regression with ANOVA decomposition kernels / Mark O. Stitson .. [et al.] -- Support vector density estimation / Jason Weston .. [et al.] -- Combining support vector and mathematical programming methods for classification / Kristin P. Bennett -- Kernel principal component analysis / Berhard Scho<lkopf, Alex J. Smola and Klaus-Robert Mu<ller.
530 ▼a Also available via the World Wide Web.
650 0 ▼a Machine learning.
650 0 ▼a Algorithms.
650 0 ▼a Kernel functions.
700 1 ▼a Scho<lkopf, Bernhard.
700 1 ▼a Burges, Christopher J. C.
700 1 ▼a Smola, Alexander J.

소장정보

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
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