Machine Learning and Knowledge Discovery in Databases  European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010. Proceedings, Part II /  [electronic resource] : 
edited by José L. Balcázar, Francesco Bonchi, Aristides Gionis, Michèle Sebag. 
 - 1st ed. 2010. 
 - XXI, 518 p. 145 illus.  online resource. 
 - Lecture Notes in Artificial Intelligence,  6322  2945-9141 ; .
 - Lecture Notes in Artificial Intelligence,  6322 .
<br/><br/>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. 
<br/><br/><label>ISBN: </label>9783642158834 
<br/><br/><label>Standard No.: </label>10.1007/978-3-642-15883-4  doi 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Artificial intelligence.<br/>Data structures (Computer science).<br/>Information theory.<br/>Application software.<br/>Information storage and retrieval systems.<br/>Database management.<br/>Data mining.<br/>Artificial Intelligence.<br/>Data Structures and Information Theory.<br/>Computer and Information Systems Applications.<br/>Information Storage and Retrieval.<br/>Database Management.<br/>Data Mining and Knowledge Discovery.
<br/><br/><label>LC Class. No.: </label>Q334-342 TA347.A78 
<br/><br/><label>Dewey Class. No.: </label>006.3