Advances in kernel methods :: support vector learning /
Gespeichert in:
| Weitere Verfasser: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge, Mass. :
MIT Press,
©1999.
©1999 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | 1 online resource (vii, 376 pages) : illustrations |
| Bibliographie: | Includes bibliographical references (pages 353-371) and index. |
| ISBN: | 0585128294 9780585128290 9780262194167 0262194163 9780262283199 0262283190 |
Internformat
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| 245 | 0 | 0 | |a Advances in kernel methods : |b support vector learning / |c edited by Bernhard Schölkopf, Christopher J.C. Burges, Alexander J. Smola. |
| 260 | |a Cambridge, Mass. : |b MIT Press, |c ©1999. | ||
| 264 | 4 | |c ©1999 | |
| 300 | |a 1 online resource (vii, 376 pages) : |b illustrations | ||
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| 504 | |a Includes bibliographical references (pages 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 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 . [and others] -- 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. | |
| 588 | 0 | |a Print version record. | |
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| 650 | 0 | |a Algorithms. |0 http://id.loc.gov/authorities/subjects/sh85003487 | |
| 650 | 0 | |a Kernel functions. |0 http://id.loc.gov/authorities/subjects/sh85072061 | |
| 650 | 2 | |a Algorithms |0 https://id.nlm.nih.gov/mesh/D000465 | |
| 650 | 2 | |a Machine Learning |0 https://id.nlm.nih.gov/mesh/D000069550 | |
| 650 | 6 | |a Apprentissage automatique. | |
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| 700 | 1 | |a Smola, Alexander J. |0 http://id.loc.gov/authorities/names/n98071321 | |
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| adam_text | |
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| author2 | Schölkopf, Bernhard Burges, Christopher J. C. Smola, Alexander J. |
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| author_facet | Schölkopf, Bernhard Burges, Christopher J. C. Smola, Alexander J. |
| author_sort | Schölkopf, Bernhard |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | Q - Science |
| callnumber-label | Q325 |
| callnumber-raw | Q325.5 .A32 1999eb |
| callnumber-search | Q325.5 .A32 1999eb |
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| contents | 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 . [and others] -- 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. |
| ctrlnum | (OCoLC)44957981 |
| dewey-full | 006.3/1 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3/1 |
| dewey-search | 006.3/1 |
| dewey-sort | 16.3 11 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
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| genre | Congressen (vorm) (NL-LeOCL)088142469 gtt |
| genre_facet | Congressen (vorm) |
| id | ZDB-4-EBU-ocm44957981 |
| illustrated | Illustrated |
| indexdate | 2024-11-26T14:48:55Z |
| institution | BVB |
| isbn | 0585128294 9780585128290 9780262194167 0262194163 9780262283199 0262283190 |
| language | English |
| oclc_num | 44957981 |
| open_access_boolean | |
| owner | MAIN DE-863 DE-BY-FWS |
| owner_facet | MAIN DE-863 DE-BY-FWS |
| physical | 1 online resource (vii, 376 pages) : illustrations |
| psigel | ZDB-4-EBU |
| publishDate | 1999 |
| publishDateSearch | 1999 |
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| publisher | MIT Press, |
| record_format | marc |
| spelling | Advances in kernel methods : support vector learning / edited by Bernhard Schölkopf, Christopher J.C. Burges, Alexander J. Smola. Cambridge, Mass. : MIT Press, ©1999. ©1999 1 online resource (vii, 376 pages) : illustrations text txt rdacontent computer c rdamedia online resource cr rdacarrier data file 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 . [and others] -- 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. Print version record. English. Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Algorithms. http://id.loc.gov/authorities/subjects/sh85003487 Kernel functions. http://id.loc.gov/authorities/subjects/sh85072061 Algorithms https://id.nlm.nih.gov/mesh/D000465 Machine Learning https://id.nlm.nih.gov/mesh/D000069550 Apprentissage automatique. Algorithmes. Noyaux (Mathématiques) algorithms. aat 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) (NL-LeOCL)078510333 gtt Machine-learning. gtt Congressen (vorm) (NL-LeOCL)088142469 gtt Schölkopf, Bernhard. http://id.loc.gov/authorities/names/n98071318 Burges, Christopher J. C. http://id.loc.gov/authorities/names/n98071320 Smola, Alexander J. http://id.loc.gov/authorities/names/n98071321 has work: Advances in kernel methods (Text) https://id.oclc.org/worldcat/entity/E39PCGt98kDjvVJMbHpHqvQ76q https://id.oclc.org/worldcat/ontology/hasWork Print version: Advances in kernel methods. Cambridge, Mass. : MIT Press, ©1999 0262194163 (DLC) 98040302 (OCoLC)39706952 FWS01 ZDB-4-EBU FWS_PDA_EBU https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=421 Volltext |
| spellingShingle | Advances in kernel methods : support vector learning / 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 . [and others] -- 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. Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Algorithms. http://id.loc.gov/authorities/subjects/sh85003487 Kernel functions. http://id.loc.gov/authorities/subjects/sh85072061 Algorithms https://id.nlm.nih.gov/mesh/D000465 Machine Learning https://id.nlm.nih.gov/mesh/D000069550 Apprentissage automatique. Algorithmes. Noyaux (Mathématiques) algorithms. aat 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) (NL-LeOCL)078510333 gtt Machine-learning. gtt |
| subject_GND | http://id.loc.gov/authorities/subjects/sh85079324 http://id.loc.gov/authorities/subjects/sh85003487 http://id.loc.gov/authorities/subjects/sh85072061 https://id.nlm.nih.gov/mesh/D000465 https://id.nlm.nih.gov/mesh/D000069550 (NL-LeOCL)078510333 (NL-LeOCL)088142469 |
| 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 | Machine learning. http://id.loc.gov/authorities/subjects/sh85079324 Algorithms. http://id.loc.gov/authorities/subjects/sh85003487 Kernel functions. http://id.loc.gov/authorities/subjects/sh85072061 Algorithms https://id.nlm.nih.gov/mesh/D000465 Machine Learning https://id.nlm.nih.gov/mesh/D000069550 Apprentissage automatique. Algorithmes. Noyaux (Mathématiques) algorithms. aat 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) (NL-LeOCL)078510333 gtt Machine-learning. gtt |
| topic_facet | Machine learning. Algorithms. Kernel functions. Algorithms Machine Learning Apprentissage automatique. Algorithmes. Noyaux (Mathématiques) algorithms. COMPUTERS Enterprise Applications Business Intelligence Tools. COMPUTERS Intelligence (AI) & Semantics. Kernel functions Machine learning Kunstmatige intelligentie. Algoritmen. Patroonherkenning. Functies (wiskunde) Machine-learning. Congressen (vorm) |
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