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Advanced Lectures on Machine Learning [[electronic resource] ] : Machine Learning Summer School 2002, Canberra, Australia, February 11-22, 2002, Revised Lectures / / edited by Shahar Mendelson, Alexander J. Smola
| Advanced Lectures on Machine Learning [[electronic resource] ] : Machine Learning Summer School 2002, Canberra, Australia, February 11-22, 2002, Revised Lectures / / edited by Shahar Mendelson, Alexander J. Smola |
| Edizione | [1st ed. 2003.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003 |
| Descrizione fisica | 1 online resource (X, 266 p.) |
| Disciplina | 006.3/1 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Social sciences Humanities Computer science Algorithms Artificial Intelligence Humanities and Social Sciences Theory of Computation |
| ISBN | 3-540-36434-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Few Notes on Statistical Learning Theory -- A Short Introduction to Learning with Kernels -- Bayesian Kernel Methods -- An Introduction to Boosting and Leveraging -- An Introduction to Reinforcement Learning Theory: Value Function Methods -- Learning Comprehensible Theories from Structured Data -- Algorithms for Association Rules -- Online Learning of Linear Classifiers. |
| Record Nr. | UNISA-996465288203316 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Advanced Lectures on Machine Learning : Machine Learning Summer School 2002, Canberra, Australia, February 11-22, 2002, Revised Lectures / / edited by Shahar Mendelson, Alexander J. Smola
| Advanced Lectures on Machine Learning : Machine Learning Summer School 2002, Canberra, Australia, February 11-22, 2002, Revised Lectures / / edited by Shahar Mendelson, Alexander J. Smola |
| Edizione | [1st ed. 2003.] |
| Pubbl/distr/stampa | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003 |
| Descrizione fisica | 1 online resource (X, 266 p.) |
| Disciplina | 006.3/1 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Social sciences Humanities Computer science Algorithms Artificial Intelligence Humanities and Social Sciences Theory of Computation |
| ISBN | 3-540-36434-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Few Notes on Statistical Learning Theory -- A Short Introduction to Learning with Kernels -- Bayesian Kernel Methods -- An Introduction to Boosting and Leveraging -- An Introduction to Reinforcement Learning Theory: Value Function Methods -- Learning Comprehensible Theories from Structured Data -- Algorithms for Association Rules -- Online Learning of Linear Classifiers. |
| Record Nr. | UNINA-9910143880003321 |
| Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Debating the Good Society : a Quest to Bridge America's Moral Divide
| Debating the Good Society : a Quest to Bridge America's Moral Divide |
| Autore | Scholkpf Bernhard |
| Pubbl/distr/stampa | Cambridge, : MIT Press, 2015 |
| Descrizione fisica | 1 online resource (371 p.) |
| Disciplina | 306.0973 |
| Altri autori (Persone) |
SmolaAlexander J
BurgesChristopher J |
| Soggetto topico | Social values - United States |
| Soggetto non controllato |
SOCIAL SCIENCES/Political Science/Political & Social Theory
SOCIAL SCIENCES/Political Science/General |
| ISBN |
0-262-26453-6
0-262-28317-4 0-585-07794-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | ""Contents""; ""Introduction""; ""Interlude""; ""Does the Well-Ordered Soul Develop Naturally?""; ""The Question of the Adequacy of the Human Being""; ""Interlude""; ""Must People, to Be Good, Submit to Authority?""; ""Can a Good Order Be Based on Hierarchy?""; ""Interlude""; ""Do We Have the Moorings We Need?""; ""When Bad Things Happen Because of Good People""; ""Interlude""; ""What Does This Creation Say about the Creator?""; ""Interlude""; ""An Evolutionary View of Order""; ""Interlude""; ""How Can Good Order Be Built from What We Can Know of Truth?""; ""Conclusion""; ""Notes"" |
| Record Nr. | UNINA-9910778639803321 |
Scholkpf Bernhard
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| Cambridge, : MIT Press, 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Learning with kernels : support vector machines, regularization, optimization, and beyond / / Bernhard Scholkopf, Alexander J. Smola
| Learning with kernels : support vector machines, regularization, optimization, and beyond / / Bernhard Scholkopf, Alexander J. Smola |
| Autore | Scholkopf Bernhard |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cambridge, Mass., : MIT Press, c2002 |
| Descrizione fisica | 1 online resource (645 p.) |
| Disciplina | 006.3/1 |
| Altri autori (Persone) | SmolaAlexander J |
| Collana | Adaptive computation and machine learning |
| Soggetto topico |
Machine learning
Algorithms Kernel functions |
| ISBN |
0-262-25693-2
0-585-47759-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents; Series Foreword; Preface; 1 - A Tutorial Introduction; I - Concepts and Tools; 2 - Kernels; 3 - Risk and Loss Functions; 4 - Regularization; 5 - Elements of Statistical Learning Theory; 6 - Optimization; II - Support Vector Machines; 7 - Pattern Recognition; 8 - Single-Class Problems: Quantile Estimation and Novelty Detection; 9 - Regression Estimation; 10 - Implementation; 11 - Incorporating Invariances; 12 - Learning Theory Revisited; III - Kernel Methods; 13 - Designing Kernels; 14 - Kernel Feature Extraction; 15 - Kernel Fisher Discriminant; 16 - Bayesian Kernel Methods
17 - Regularized Principal Manifolds18 - Pre-Images and Reduced Set Methods; A - Addenda; B - Mathematical Prerequisites; References; Index; Notation and Symbols |
| Record Nr. | UNINA-9910822339903321 |
|
Scholkopf Bernhard
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| Cambridge, Mass., : MIT Press, c2002 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Learning with kernels : support vector machines, regularization, optimization, and beyond / / Bernhard Schölkopf, Alexander J. Smola
| Learning with kernels : support vector machines, regularization, optimization, and beyond / / Bernhard Schölkopf, Alexander J. Smola |
| Autore | Schölkopf Bernhard |
| Pubbl/distr/stampa | Cambridge, Mass., : MIT Press, ©2002 |
| Descrizione fisica | 1 online resource (645 p.) |
| Disciplina | 006.3/1 |
| Altri autori (Persone) | SmolaAlexander J |
| Collana | Adaptive computation and machine learning |
| Soggetto topico |
Machine learning
Algorithms Kernel functions |
| Soggetto non controllato | COMPUTER SCIENCE/Machine Learning & Neural Networks |
| ISBN |
0-262-25693-2
0-585-47759-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents; Series Foreword; Preface; 1 - A Tutorial Introduction; I - Concepts and Tools; 2 - Kernels; 3 - Risk and Loss Functions; 4 - Regularization; 5 - Elements of Statistical Learning Theory; 6 - Optimization; II - Support Vector Machines; 7 - Pattern Recognition; 8 - Single-Class Problems: Quantile Estimation and Novelty Detection; 9 - Regression Estimation; 10 - Implementation; 11 - Incorporating Invariances; 12 - Learning Theory Revisited; III - Kernel Methods; 13 - Designing Kernels; 14 - Kernel Feature Extraction; 15 - Kernel Fisher Discriminant; 16 - Bayesian Kernel Methods
17 - Regularized Principal Manifolds18 - Pre-Images and Reduced Set Methods; A - Addenda; B - Mathematical Prerequisites; References; Index; Notation and Symbols |
| Record Nr. | UNINA-9910780260003321 |
|
Schölkopf Bernhard
|
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| Cambridge, Mass., : MIT Press, ©2002 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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