top

  Info

  • Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.

  Info

  • Utilizzare questo link per rimuovere la selezione effettuata.
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010. Proceedings, Part I / / edited by José L. Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010. Proceedings, Part I / / edited by José L. Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag
Edizione [1st ed. 2010.]
Pubbl/distr/stampa Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010
Descrizione fisica 1 online resource (XXX, 620 p. 175 illus.)
Disciplina 006.3
Collana Lecture Notes in Artificial Intelligence
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
ISBN 1-280-38918-4
9786613567109
3-642-15880-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Invited Talks (Abstracts) -- Mining Billion-Node Graphs: Patterns, Generators and Tools -- Structure Is Informative: On Mining Structured Information Networks -- Intelligent Interaction with the Real World -- Mining Experimental Data for Dynamical Invariants - From Cognitive Robotics to Computational Biology -- Hierarchical Learning Machines and Neuroscience of Visual Cortex -- Formal Theory of Fun and Creativity -- Regular Papers -- Porting Decision Tree Algorithms to Multicore Using FastFlow -- On Classifying Drifting Concepts in P2P Networks -- A Unified Approach to Active Dual Supervision for Labeling Features and Examples -- Vector Field Learning via Spectral Filtering -- Weighted Symbols-Based Edit Distance for String-Structured Image Classification -- A Concise Representation of Association Rules Using Minimal Predictive Rules -- Euclidean Distances, Soft and Spectral Clustering on Weighted Graphs -- Adaptive Parallel/Serial Sampling Mechanisms for Particle Filtering in Dynamic Bayesian Networks -- Leveraging Bagging for Evolving Data Streams -- ITCH: Information-Theoretic Cluster Hierarchies -- Coniunge et Impera: Multiple-Graph Mining for Query-Log Analysis -- Process Mining Meets Abstract Interpretation -- Smarter Sampling in Model-Based Bayesian Reinforcement Learning -- Predicting Partial Orders: Ranking with Abstention -- Predictive Distribution Matching SVM for Multi-domain Learning -- Kantorovich Distances between Rankings with Applications to Rank Aggregation -- Characteristic Kernels on Structured Domains Excel in Robotics and Human Action Recognition -- Regret Analysis for Performance Metrics in Multi-Label Classification: The Case of Hamming and Subset Zero-One Loss -- Clustering Vessel Trajectories with Alignment Kernels under Trajectory Compression -- Adaptive Bases for Reinforcement Learning -- Constructing Nonlinear Discriminants from Multiple Data Views -- Learning Algorithms for Link Prediction Based on Chance Constraints -- Sparse Unsupervised Dimensionality Reduction Algorithms -- Asking Generalized Queries to Ambiguous Oracle -- Analysis of Large Multi-modal Social Networks: Patterns and a Generator -- A Cluster-Level Semi-supervision Model for Interactive Clustering -- Software-Defect Localisation by Mining Dataflow-Enabled Call Graphs -- Induction of Concepts in Web Ontologies through Terminological Decision Trees -- Classification with Sums of Separable Functions -- Feature Selection for Reinforcement Learning: Evaluating Implicit State-Reward Dependency via Conditional Mutual Information -- Bagging for Biclustering: Application to Microarray Data -- Hub Gene Selection Methods for the Reconstruction of Transcription Networks -- Expectation Propagation for Bayesian Multi-task Feature Selection -- Graphical Multi-way Models -- Exploration-Exploitation of Eye Movement Enriched Multiple Feature Spaces for Content-Based Image Retrieval -- Graph Regularized Transductive Classification on Heterogeneous Information Networks -- Temporal Maximum Margin Markov Network -- Gaussian Processes for Sample Efficient Reinforcement Learning with RMAX-Like Exploration.
Record Nr. UNISA-996466569903316
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
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
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
Edizione [1st ed. 2010.]
Pubbl/distr/stampa Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010
Descrizione fisica 1 online resource (XXII, 632 p. 183 illus.)
Disciplina 006.3
Collana Lecture Notes in Artificial Intelligence
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
ISBN 1-280-38926-5
9786613567185
3-642-15939-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
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.
Record Nr. UNISA-996466569603316
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010. Proceedings, Part II / / edited by José L. Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010. Proceedings, Part II / / edited by José L. Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag
Edizione [1st ed. 2010.]
Pubbl/distr/stampa Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010
Descrizione fisica 1 online resource (XXI, 518 p. 145 illus.)
Disciplina 006.3
Collana Lecture Notes in Artificial Intelligence
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
ISBN 1-280-38919-2
9786613567116
3-642-15883-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Regular Papers -- Bayesian Knowledge Corroboration with Logical Rules and User Feedback -- Learning an Affine Transformation for Non-linear Dimensionality Reduction -- NDPMine: Efficiently Mining Discriminative Numerical Features for Pattern-Based Classification -- Hidden Conditional Ordinal Random Fields for Sequence Classification -- A Unifying View of Multiple Kernel Learning -- Evolutionary Dynamics of Regret Minimization -- Recognition of Instrument Timbres in Real Polytimbral Audio Recordings -- Finding Critical Nodes for Inhibiting Diffusion of Complex Contagions in Social Networks -- Semi-supervised Abstraction-Augmented String Kernel for Multi-level Bio-Relation Extraction -- Online Knowledge-Based Support Vector Machines -- Learning with Randomized Majority Votes -- Exploration in Relational Worlds -- Efficient Confident Search in Large Review Corpora -- Learning to Tag from Open Vocabulary Labels -- A Robustness Measure of Association Rules -- Automatic Model Adaptation for Complex Structured Domains -- Collective Traffic Forecasting -- On Detecting Clustered Anomalies Using SCiForest -- Constrained Parameter Estimation for Semi-supervised Learning: The Case of the Nearest Mean Classifier -- Online Learning in Adversarial Lipschitz Environments -- Summarising Data by Clustering Items -- Classification and Novel Class Detection of Data Streams in a Dynamic Feature Space -- Latent Structure Pattern Mining -- First-Order Bayes-Ball -- Learning from Demonstration Using MDP Induced Metrics -- Demand-Driven Tag Recommendation -- Solving Structured Sparsity Regularization with Proximal Methods -- Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models -- Improved MinMax Cut Graph Clustering with Nonnegative Relaxation -- Integrating Constraint Programming and Itemset Mining -- Topic Modeling for Personalized Recommendation of Volatile Items -- Conditional Ranking on Relational Data.
Record Nr. UNISA-996466570403316
Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2010
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui