Vai al contenuto principale della pagina

Partially Supervised Learning : Second IAPR International Workshop, PSL 2013, Nanjing, China, May 13-14, 2013, Revised Selected Papers / / edited by Zhi-Hua Zhou, Friedhelm Schwenker



(Visualizza in formato marc)    (Visualizza in BIBFRAME)

Titolo: Partially Supervised Learning : Second IAPR International Workshop, PSL 2013, Nanjing, China, May 13-14, 2013, Revised Selected Papers / / edited by Zhi-Hua Zhou, Friedhelm Schwenker Visualizza cluster
Pubblicazione: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2013
Edizione: 1st ed. 2013.
Descrizione fisica: 1 online resource (IX, 117 p. 34 illus.)
Disciplina: 004
Soggetto topico: Data mining
Pattern recognition systems
Artificial intelligence
Data Mining and Knowledge Discovery
Automated Pattern Recognition
Artificial Intelligence
Persona (resp. second.): ZhouZhi-Hua
SchwenkerFriedhelm
Note generali: Bibliographic Level Mode of Issuance: Monograph
Nota di contenuto: Partially Supervised Anomaly Detection using Convex Hulls on a 2D Parameter Space -- Self-Practice Imitation Learning from Weak Policy -- Semi-Supervised Dictionary Learning of Sparse Representations for Emotion Recognition -- Adaptive Graph Constrained NMF for Semi-Supervised Learning -- Kernel Parameter Optimization in Stretched Kernel-based Fuzzy Clustering -- Conscientiousness Measurement from Weibo’s Public Information -- Meta-Learning of Exploration and Exploitation Parameters with Replacing Eligibility Traces -- Neighborhood Co-regularized Multi-view Spectral Clustering of Microbiome Data -- A Robust Image Watermarking Scheme Based on BWT and ICA -- A New Weighted Sparse Representation Based on MSLBP and Its Application to Face Recognition.
Sommario/riassunto: This book constitutes the thoroughly refereed revised selected papers from the Second IAPR International Workshop, PSL 2013, held in Nanjing, China, in May 2013. The 10 papers included in this volume were carefully reviewed and selected from 26 submissions. Partially supervised learning is a rapidly evolving area of machine learning. It generalizes many kinds of learning paradigms including supervised and unsupervised learning, semi-supervised learning for classification and regression, transductive learning, semi-supervised clustering, multi-instance learning, weak label learning, policy learning in partially observable environments, etc.
Titolo autorizzato: Partially Supervised Learning  Visualizza cluster
ISBN: 3-642-40705-6
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910484162203321
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Serie: Lecture Notes in Artificial Intelligence, . 2945-9141 ; ; 8183