Subspace, Latent Structure and Feature Selection [[electronic resource] ] : Statistical and Optimization Perspectives Workshop, SLSFS 2005 Bohinj, Slovenia, February 23-25, 2005, Revised Selected Papers / / edited by Craig Saunders, Marko Grobelnik, Steve Gunn, John Shawe-Taylor
(Visualizza in formato marc)
(Visualizza in BIBFRAME)
| Titolo: |
Subspace, Latent Structure and Feature Selection [[electronic resource] ] : Statistical and Optimization Perspectives Workshop, SLSFS 2005 Bohinj, Slovenia, February 23-25, 2005, Revised Selected Papers / / edited by Craig Saunders, Marko Grobelnik, Steve Gunn, John Shawe-Taylor
|
| Pubblicazione: | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 |
| Edizione: | 1st ed. 2006. |
| Descrizione fisica: | 1 online resource (X, 209 p.) |
| Disciplina: | 003/.1 |
| Soggetto topico: | Algorithms |
| Computer science—Mathematics | |
| Mathematical statistics | |
| Computer science | |
| Artificial intelligence | |
| Computer vision | |
| Pattern recognition systems | |
| Probability and Statistics in Computer Science | |
| Theory of Computation | |
| Artificial Intelligence | |
| Computer Vision | |
| Automated Pattern Recognition | |
| Persona (resp. second.): | SaundersCraig |
| GrobelnikMarko | |
| GunnSteve | |
| Shawe-TaylorJohn | |
| Note generali: | Bibliographic Level Mode of Issuance: Monograph |
| Nota di bibliografia: | Includes bibliographical references and author index. |
| Nota di contenuto: | Invited Contributions -- Discrete Component Analysis -- Overview and Recent Advances in Partial Least Squares -- Random Projection, Margins, Kernels, and Feature-Selection -- Some Aspects of Latent Structure Analysis -- Feature Selection for Dimensionality Reduction -- Contributed Papers -- Auxiliary Variational Information Maximization for Dimensionality Reduction -- Constructing Visual Models with a Latent Space Approach -- Is Feature Selection Still Necessary? -- Class-Specific Subspace Discriminant Analysis for High-Dimensional Data -- Incorporating Constraints and Prior Knowledge into Factorization Algorithms – An Application to 3D Recovery -- A Simple Feature Extraction for High Dimensional Image Representations -- Identifying Feature Relevance Using a Random Forest -- Generalization Bounds for Subspace Selection and Hyperbolic PCA -- Less Biased Measurement of Feature Selection Benefits. |
| Titolo autorizzato: | Subspace, Latent Structure and Feature Selection |
| ISBN: | 3-540-34138-2 |
| Formato: | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 996465879603316 |
| Lo trovi qui: | Univ. di Salerno |
| Opac: | Controlla la disponibilità qui |
Serie:
Theoretical Computer Science and General Issues, . 2512-2029 ; ; 3940