Machine Learning and Knowledge Discovery in Databases [electronic resource] : European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part III / edited by Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip ʻeleznȻ.

Por: Blockeel, Hendrik [editor.]Colaborador(es): Kersting, Kristian [editor.] | Nijssen, Siegfried [editor.] | ʻeleznȻ, Filip [editor.]Tipo de material: TextoTextoSeries Lecture Notes in Computer Science, 8190Editor: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013Descripción: XLVI, 691 p. 190 illus. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783642409943Trabajos contenidos: SpringerLink (Online service)Tema(s): Computer science | Computational complexity | Data mining | Information storage and retrieval systems | Artificial intelligence | Optical pattern recognition | Computer Science | Data Mining and Knowledge Discovery | Artificial Intelligence (incl. Robotics) | Pattern Recognition | Discrete Mathematics in Computer Science | Probability and Statistics in Computer Science | Information Storage and RetrievalFormatos físicos adicionales: Sin títuloClasificación CDD: 006.312 Clasificación LoC:QA76.9.D343Recursos en línea: de clik aquí para ver el libro electrónico
Contenidos:
Springer eBooksResumen: This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013, held in Prague, Czech Republic, in September 2013. The 111 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 447 submissions. The papers are organized in topical sections on reinforcement learning; Markov decision processes; active learning and optimization; learning from sequences; time series and spatio-temporal data; data streams; graphs and networks; social network analysis; natural language processing and information extraction; ranking and recommender systems; matrix and tensor analysis; structured output prediction, multi-label and multi-task learning; transfer learning; bayesian learning; graphical models; nearest-neighbor methods; ensembles; statistical learning; semi-supervised learning; unsupervised learning; subgroup discovery, outlier detection and anomaly detection; privacy and security; evaluation; applications; and medical applications.
Etiquetas de esta biblioteca: No hay etiquetas de esta biblioteca para este título. Ingresar para agregar etiquetas.
    Valoración media: 0.0 (0 votos)
No hay ítems correspondientes a este registro

Reinforcement learning -- Markov decision processes -- Active learning and optimization -- Learning from sequences -- Time series and spatio-temporal data -- Data streams -- Graphs and networks -- Social network analysis -- Natural language processing and information extraction -- Ranking and recommender systems -- Matrix and tensor analysis -- Structured output prediction, multi-label and multi-task learning -- Transfer learning -- Bayesian learning -- Graphical models -- Nearest-neighbor methods -- Ensembles -- Statistical learning -- Semi-supervised learning -- Unsupervised learning -- Subgroup discovery, outlier detection and anomaly detection -- Privacy and security -- Evaluation -- Applications -- Medical applications.

This three-volume set LNAI 8188, 8189 and 8190 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2013, held in Prague, Czech Republic, in September 2013. The 111 revised research papers presented together with 5 invited talks were carefully reviewed and selected from 447 submissions. The papers are organized in topical sections on reinforcement learning; Markov decision processes; active learning and optimization; learning from sequences; time series and spatio-temporal data; data streams; graphs and networks; social network analysis; natural language processing and information extraction; ranking and recommender systems; matrix and tensor analysis; structured output prediction, multi-label and multi-task learning; transfer learning; bayesian learning; graphical models; nearest-neighbor methods; ensembles; statistical learning; semi-supervised learning; unsupervised learning; subgroup discovery, outlier detection and anomaly detection; privacy and security; evaluation; applications; and medical applications.

No hay comentarios en este titulo.

para colocar un comentario.