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.

Πίνακας περιεχομένων:

• 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.