Advances in kernel methods: support vector learning
Gespeichert in:
| Format: | Elektronisch E-Book |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Cambridge, Mass.
MIT Press
©1999
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | Includes bibliographical references (pages 353-371) and index 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 Schölkopf -- 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 Müller . [and others] -- 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 . [and others] -- 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 Schölkopf, Alex J. Smola and Klaus-Robert Müller |
| Beschreibung: | 1 Online-Ressource (vii, 376 pages) |
| ISBN: | 0585128294 9780585128290 0262194163 9780262194167 |
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| 264 | 1 | |a Cambridge, Mass. |b MIT Press |c ©1999 | |
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Datensatz im Suchindex
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| indexdate | 2024-07-10T07:14:02Z |
| institution | BVB |
| isbn | 0585128294 9780585128290 0262194163 9780262194167 |
| language | English |
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| spelling | Advances in kernel methods support vector learning edited by Bernhard Schölkopf, Christopher J.C. Burges, Alexander J. Smola Cambridge, Mass. MIT Press ©1999 1 Online-Ressource (vii, 376 pages) txt rdacontent c rdamedia cr rdacarrier Includes bibliographical references (pages 353-371) and index 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 Schölkopf -- 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 Müller . [and others] -- 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 . [and others] -- 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 Schölkopf, Alex J. Smola and Klaus-Robert Müller Algorithms Machine learning Kernel functions COMPUTERS / Enterprise Applications / Business Intelligence Tools bisacsh COMPUTERS / Intelligence (AI) & Semantics bisacsh Algorithms fast Kernel functions fast Machine learning fast Kunstmatige intelligentie gtt Algoritmen gtt Patroonherkenning gtt Functies (wiskunde) gtt Machine-learning gtt Support-Vektor-Maschine (DE-588)4505517-8 gnd rswk-swf 1\p (DE-588)4143413-4 Aufsatzsammlung gnd-content Support-Vektor-Maschine (DE-588)4505517-8 s 2\p DE-604 Schölkopf, Bernhard Sonstige oth Burges, Christopher J. C. Sonstige oth Smola, Alexander J. Sonstige oth http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=421 Aggregator Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Advances in kernel methods support vector learning Algorithms Machine learning Kernel functions COMPUTERS / Enterprise Applications / Business Intelligence Tools bisacsh COMPUTERS / Intelligence (AI) & Semantics bisacsh Algorithms fast Kernel functions fast Machine learning fast Kunstmatige intelligentie gtt Algoritmen gtt Patroonherkenning gtt Functies (wiskunde) gtt Machine-learning gtt Support-Vektor-Maschine (DE-588)4505517-8 gnd |
| subject_GND | (DE-588)4505517-8 (DE-588)4143413-4 |
| title | Advances in kernel methods support vector learning |
| title_auth | Advances in kernel methods support vector learning |
| title_exact_search | Advances in kernel methods support vector learning |
| title_full | Advances in kernel methods support vector learning edited by Bernhard Schölkopf, Christopher J.C. Burges, Alexander J. Smola |
| title_fullStr | Advances in kernel methods support vector learning edited by Bernhard Schölkopf, Christopher J.C. Burges, Alexander J. Smola |
| title_full_unstemmed | Advances in kernel methods support vector learning edited by Bernhard Schölkopf, Christopher J.C. Burges, Alexander J. Smola |
| title_short | Advances in kernel methods |
| title_sort | advances in kernel methods support vector learning |
| title_sub | support vector learning |
| topic | Algorithms Machine learning Kernel functions COMPUTERS / Enterprise Applications / Business Intelligence Tools bisacsh COMPUTERS / Intelligence (AI) & Semantics bisacsh Algorithms fast Kernel functions fast Machine learning fast Kunstmatige intelligentie gtt Algoritmen gtt Patroonherkenning gtt Functies (wiskunde) gtt Machine-learning gtt Support-Vektor-Maschine (DE-588)4505517-8 gnd |
| topic_facet | Algorithms Machine learning Kernel functions COMPUTERS / Enterprise Applications / Business Intelligence Tools COMPUTERS / Intelligence (AI) & Semantics Kunstmatige intelligentie Algoritmen Patroonherkenning Functies (wiskunde) Machine-learning Support-Vektor-Maschine Aufsatzsammlung |
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| work_keys_str_mv | AT scholkopfbernhard advancesinkernelmethodssupportvectorlearning AT burgeschristopherjc advancesinkernelmethodssupportvectorlearning AT smolaalexanderj advancesinkernelmethodssupportvectorlearning |