Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Semi-supervised learning / / [edited by] Olivier Chapelle, Bernhard Schölkopf, Alexander Zien
| Semi-supervised learning / / [edited by] Olivier Chapelle, Bernhard Schölkopf, Alexander Zien |
| Pubbl/distr/stampa | Cambridge, Mass., : MIT Press, ©2006 |
| Descrizione fisica | 1 online resource (528 p.) |
| Disciplina | 006.3/1 |
| Altri autori (Persone) |
ChapelleOlivier
SchölkopfBernhard ZienAlexander |
| Collana | Adaptive computation and machine learning |
| Soggetto topico | Supervised learning (Machine learning) |
| Soggetto non controllato | COMPUTER SCIENCE/Machine Learning & Neural Networks |
| ISBN |
1-282-09618-4
0-262-25589-8 1-4294-1408-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents; Series Foreword; Preface; 1 - Introduction to Semi-Supervised Learning; 2 - A Taxonomy for Semi-Supervised Learning Methods; 3 - Semi-Supervised Text Classification Using EM; 4 - Risks of Semi-Supervised Learning: How Unlabeled Data Can Degrade Performance of Generative Classifiers; 5 - Probabilistic Semi-Supervised Clustering with Constraints; 6 - Transductive Support Vector Machines; 7 - Semi-Supervised Learning Using Semi- Definite Programming; 8 - Gaussian Processes and the Null-Category Noise Model; 9 - Entropy Regularization; 10 - Data-Dependent Regularization
11 - Label Propagation and Quadratic Criterion12 - The Geometric Basis of Semi-Supervised Learning; 13 - Discrete Regularization; 14 - Semi-Supervised Learning with Conditional Harmonic Mixing; 15 - Graph Kernels by Spectral Transforms; 16- Spectral Methods for Dimensionality Reduction; 17 - Modifying Distances; 18 - Large-Scale Algorithms; 19 - Semi-Supervised Protein Classification Using Cluster Kernels; 20 - Prediction of Protein Function from Networks; 21 - Analysis of Benchmarks; 22 - An Augmented PAC Model for Semi- Supervised Learning 23 - Metric-Based Approaches for Semi- Supervised Regression and Classification24 - Transductive Inference and Semi-Supervised Learning; 25 - A Discussion of Semi-Supervised Learning and Transduction; References; Notation and Symbols; Contributors; Index |
| Record Nr. | UNINA-9910777620503321 |
| Cambridge, Mass., : MIT Press, ©2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Semi-supervised learning / / [edited by] Olivier Chapelle, Bernhard Schölkopf, Alexander Zien
| Semi-supervised learning / / [edited by] Olivier Chapelle, Bernhard Schölkopf, Alexander Zien |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Cambridge, Mass., : MIT Press, c2006 |
| Descrizione fisica | 1 online resource (528 p.) |
| Disciplina | 006.3/1 |
| Altri autori (Persone) |
ChapelleOlivier
SchölkopfBernhard ZienAlexander |
| Collana | Adaptive computation and machine learning |
| Soggetto topico | Supervised learning (Machine learning) |
| ISBN |
1-282-09618-4
0-262-25589-8 1-4294-1408-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Contents; Series Foreword; Preface; 1 - Introduction to Semi-Supervised Learning; 2 - A Taxonomy for Semi-Supervised Learning Methods; 3 - Semi-Supervised Text Classification Using EM; 4 - Risks of Semi-Supervised Learning: How Unlabeled Data Can Degrade Performance of Generative Classifiers; 5 - Probabilistic Semi-Supervised Clustering with Constraints; 6 - Transductive Support Vector Machines; 7 - Semi-Supervised Learning Using Semi- Definite Programming; 8 - Gaussian Processes and the Null-Category Noise Model; 9 - Entropy Regularization; 10 - Data-Dependent Regularization
11 - Label Propagation and Quadratic Criterion12 - The Geometric Basis of Semi-Supervised Learning; 13 - Discrete Regularization; 14 - Semi-Supervised Learning with Conditional Harmonic Mixing; 15 - Graph Kernels by Spectral Transforms; 16- Spectral Methods for Dimensionality Reduction; 17 - Modifying Distances; 18 - Large-Scale Algorithms; 19 - Semi-Supervised Protein Classification Using Cluster Kernels; 20 - Prediction of Protein Function from Networks; 21 - Analysis of Benchmarks; 22 - An Augmented PAC Model for Semi- Supervised Learning 23 - Metric-Based Approaches for Semi- Supervised Regression and Classification24 - Transductive Inference and Semi-Supervised Learning; 25 - A Discussion of Semi-Supervised Learning and Transduction; References; Notation and Symbols; Contributors; Index |
| Record Nr. | UNINA-9910963198603321 |
| Cambridge, Mass., : MIT Press, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||