Machine Learning and Knowledge Discovery in Databases European Conference, ECML PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I /

This book constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008. The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected f...

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Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Daelemans, Walter (Επιμελητής έκδοσης), Goethals, Bart (Επιμελητής έκδοσης), Morik, Katharina (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.
Σειρά:Lecture Notes in Computer Science, 5211
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Invited Talks (Abstracts)
  • Industrializing Data Mining, Challenges and Perspectives
  • From Microscopy Images to Models of Cellular Processes
  • Data Clustering: 50 Years Beyond K-means
  • Learning Language from Its Perceptual Context
  • The Role of Hierarchies in Exploratory Data Mining
  • Machine Learning Journal Abstracts
  • Rollout Sampling Approximate Policy Iteration
  • New Closed-Form Bounds on the Partition Function
  • Large Margin vs. Large Volume in Transductive Learning
  • Incremental Exemplar Learning Schemes for Classification on Embedded Devices
  • A Collaborative Filtering Framework Based on Both Local User Similarity and Global User Similarity
  • A Critical Analysis of Variants of the AUC
  • Improving Maximum Margin Matrix Factorization
  • Data Mining and Knowledge Discovery Journal Abstracts
  • Finding Reliable Subgraphs from Large Probabilistic Graphs
  • A Space Efficient Solution to the Frequent String Mining Problem for Many Databases
  • The Boolean Column and Column-Row Matrix Decompositions
  • SkyGraph: An Algorithm for Important Subgraph Discovery in Relational Graphs
  • Mining Conjunctive Sequential Patterns
  • Adequate Condensed Representations of Patterns
  • Two Heads Better Than One: Pattern Discovery in Time-Evolving Multi-aspect Data
  • Regular Papers
  • TOPTMH: Topology Predictor for Transmembrane ?-Helices
  • Learning to Predict One or More Ranks in Ordinal Regression Tasks
  • Cascade RSVM in Peer-to-Peer Networks
  • An Algorithm for Transfer Learning in a Heterogeneous Environment
  • Minimum-Size Bases of Association Rules
  • Combining Classifiers through Triplet-Based Belief Functions
  • An Improved Multi-task Learning Approach with Applications in Medical Diagnosis
  • Semi-supervised Laplacian Regularization of Kernel Canonical Correlation Analysis
  • Sequence Labelling SVMs Trained in One Pass
  • Semi-supervised Classification from Discriminative Random Walks
  • Learning Bidirectional Similarity for Collaborative Filtering
  • Bootstrapping Information Extraction from Semi-structured Web Pages
  • Online Multiagent Learning against Memory Bounded Adversaries
  • Scalable Feature Selection for Multi-class Problems
  • Learning Decision Trees for Unbalanced Data
  • Credal Model Averaging: An Extension of Bayesian Model Averaging to Imprecise Probabilities
  • A Fast Method for Training Linear SVM in the Primal
  • On the Equivalence of the SMO and MDM Algorithms for SVM Training
  • Nearest Neighbour Classification with Monotonicity Constraints
  • Modeling Transfer Relationships Between Learning Tasks for Improved Inductive Transfer
  • Mining Edge-Weighted Call Graphs to Localise Software Bugs
  • Hierarchical Distance-Based Conceptual Clustering
  • Mining Frequent Connected Subgraphs Reducing the Number of Candidates
  • Unsupervised Riemannian Clustering of Probability Density Functions
  • Online Manifold Regularization: A New Learning Setting and Empirical Study
  • A Fast Algorithm to Find Overlapping Communities in Networks
  • A Case Study in Sequential Pattern Mining for IT-Operational Risk
  • Tight Optimistic Estimates for Fast Subgroup Discovery
  • Watch, Listen & Learn: Co-training on Captioned Images and Videos
  • Parameter Learning in Probabilistic Databases: A Least Squares Approach
  • Improving k-Nearest Neighbour Classification with Distance Functions Based on Receiver Operating Characteristics
  • One-Class Classification by Combining Density and Class Probability Estimation
  • Efficient Frequent Connected Subgraph Mining in Graphs of Bounded Treewidth
  • Proper Model Selection with Significance Test
  • A Projection-Based Framework for Classifier Performance Evaluation
  • Distortion-Free Nonlinear Dimensionality Reduction
  • Learning with L q? vs L 1-Norm Regularisation with Exponentially Many Irrelevant Features
  • Catenary Support Vector Machines
  • Exact and Approximate Inference for Annotating Graphs with Structural SVMs
  • Extracting Semantic Networks from Text Via Relational Clustering
  • Ranking the Uniformity of Interval Pairs
  • Multiagent Reinforcement Learning for Urban Traffic Control Using Coordination Graphs
  • StreamKrimp: Detecting Change in Data Streams.