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Titolo: | Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010. Proceedings, Part III / / edited by José L. Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag |
Pubblicazione: | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010 |
Edizione: | 1st ed. 2010. |
Descrizione fisica: | 1 online resource (XXII, 632 p. 183 illus.) |
Disciplina: | 006.3 |
Soggetto topico: | Artificial intelligence |
Data structures (Computer science) | |
Application software | |
Information storage and retrieval | |
Database management | |
Data mining | |
Artificial Intelligence | |
Data Structures and Information Theory | |
Information Systems Applications (incl. Internet) | |
Information Storage and Retrieval | |
Database Management | |
Data Mining and Knowledge Discovery | |
Persona (resp. second.): | BalcázarJosé L |
BonchiFrancesco | |
GionisAristides | |
SebagMichèle | |
Note generali: | Bibliographic Level Mode of Issuance: Monograph |
Nota di bibliografia: | Includes bibliographical references and index. |
Nota di contenuto: | Regular Papers -- Efficient Planning in Large POMDPs through Policy Graph Based Factorized Approximations -- Unsupervised Trajectory Sampling -- Fast Extraction of Locally Optimal Patterns Based on Consistent Pattern Function Variations -- Large Margin Learning of Bayesian Classifiers Based on Gaussian Mixture Models -- Learning with Ensembles of Randomized Trees : New Insights -- Entropy and Margin Maximization for Structured Output Learning -- Virus Propagation on Time-Varying Networks: Theory and Immunization Algorithms -- Adapting Decision DAGs for Multipartite Ranking -- Fast and Scalable Algorithms for Semi-supervised Link Prediction on Static and Dynamic Graphs -- Modeling Relations and Their Mentions without Labeled Text -- An Efficient and Scalable Algorithm for Local Bayesian Network Structure Discovery -- Selecting Information Diffusion Models over Social Networks for Behavioral Analysis -- Learning Sparse Gaussian Markov Networks Using a Greedy Coordinate Ascent Approach -- Online Structural Graph Clustering Using Frequent Subgraph Mining -- Large-Scale Support Vector Learning with Structural Kernels -- Synchronization Based Outlier Detection -- Laplacian Spectrum Learning -- k-Version-Space Multi-class Classification Based on k-Consistency Tests -- Complexity Bounds for Batch Active Learning in Classification -- Semi-supervised Projection Clustering with Transferred Centroid Regularization -- Permutation Testing Improves Bayesian Network Learning -- Example-dependent Basis Vector Selection for Kernel-Based Classifiers -- Surprising Patterns for the Call Duration Distribution of Mobile Phone Users -- Variational Bayesian Mixture of Robust CCA Models -- Adverse Drug Reaction Mining in Pharmacovigilance Data Using Formal Concept Analysis -- Topic Models Conditioned on Relations -- Shift-Invariant Grouped Multi-task Learning for Gaussian Processes -- Nonparametric Bayesian Clustering Ensembles -- Directed Graph Learning via High-Order Co-linkage Analysis -- Incorporating Domain Models into Bayesian Optimization for RL -- Efficient and Numerically Stable Sparse Learning -- Fast Active Exploration for Link-Based Preference Learning Using Gaussian Processes -- Many-to-Many Graph Matching: A Continuous Relaxation Approach -- Competitive Online Generalized Linear Regression under Square Loss -- Cross Validation Framework to Choose amongst Models and Datasets for Transfer Learning -- Fast, Effective Molecular Feature Mining by Local Optimization -- Demo Papers -- AnswerArt - Contextualized Question Answering -- Real-Time News Recommender System -- CET: A Tool for Creative Exploration of Graphs -- NewsGist: A Multilingual Statistical News Summarizer -- QUEST: Query Expansion Using Synonyms over Time -- Flu Detector - Tracking Epidemics on Twitter -- X-SDR: An Extensible Experimentation Suite for Dimensionality Reduction -- SOREX: Subspace Outlier Ranking Exploration Toolkit -- KDTA: Automated Knowledge-Driven Text Annotation -- Detecting Events in a Million New York Times Articles -- Experience STORIES: A Visual News Search and Summarization System -- Exploring Real Mobility Data with M-Atlas. |
Titolo autorizzato: | Machine Learning and Knowledge Discovery in Databases |
ISBN: | 1-280-38926-5 |
9786613567185 | |
3-642-15939-7 | |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 996466569603316 |
Lo trovi qui: | Univ. di Salerno |
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