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

Λεπτομέρειες βιβλιογραφικής εγγραφής
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, 6321
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 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.