Machine Learning and Knowledge Discovery in Databases European Conference, ECML PKDD 2010, Barcelona, Spain, September 20-24, 2010, Proceedings, Part II /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Balcázar, José Luis (Επιμελητής έκδοσης), Bonchi, Francesco (Επιμελητής έκδοσης), Gionis, Aristides (Επιμελητής έκδοσης), Sebag, Michèle (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2010.
• Σειρά: Lecture Notes in Computer Science, 6322
• Θέματα: Computer science.; Data structures (Computer science).; Database management.; Data mining.; Information storage and retrieval.; Artificial intelligence.; Computer Science.; Artificial Intelligence (incl. Robotics).; Data Structures, Cryptology and Information Theory.; Information Systems Applications (incl. Internet).; Information Storage and Retrieval.; Database Management.; Data Mining and Knowledge Discovery.

 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.