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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
Opac: Controlla la disponibilità qui
Semi-supervised learning / / [edited by] Olivier Chapelle, Bernhard Sch?olkopf, Alexander Zien
Semi-supervised learning / / [edited by] Olivier Chapelle, Bernhard Sch?olkopf, 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
Sch?olkopfBernhard
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-9910809030503321
Cambridge, Mass., : MIT Press, c2006
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui