Machine Learning and Knowledge Discovery in Databases

Regular Papers.- Decomposition Algorithms for Training Large-Scale Semiparametric Support Vector Machines.- A Convex Method for Locating Regions of Interest with Multi-instance Learning.- Active Learning for Reward Estimation in Inverse Reinforcement Learning.- Simulated Iterative Classification A New Learning Procedure for Graph Labeling.- Graph-Based Discrete Differential Geometry for Critical Instance Filtering.- Integrating Novel Class Detection with Classification for Concept-Drifting Data Streams.- Neural Networks for State Evaluation in General Game Playing.- Learning to Disambiguate Search Queries from Short Sessions.- Dynamic Factor Graphs for Time Series Modeling.- On Feature Selection, Bias-Variance, and Bagging.- Efficient Pruning Schemes for Distance-Based Outlier Detection.- The Sensitivity of Latent Dirichlet Allocation for Information Retrieval.- Efficient Decoding of Ternary Error-Correcting Output Codes for Multiclass Classification.- The Model of Most Informative Patterns and Its Application to Knowledge Extraction from Graph Databases.- On Discriminative Parameter Learning of Bayesian Network Classifiers.- Mining Spatial Co-location Patterns with Dynamic Neighborhood Constraint.- Classifier Chains for Multi-label Classification.- Dependency Tree Kernels for Relation Extraction from Natural Language Text.- Statistical Relational Learning with Formal Ontologies.- Boosting Active Learning to Optimality: A Tractable Monte-Carlo, Billiard-Based Algorithm.- Capacity Control for Partially Ordered Feature Sets.- Reconstructing Data Perturbed by Random Projections When the Mixing Matrix Is Known.- Identifying the Original Contribution of a Document via Language Modeling.- Relaxed Transfer of Different Classes via Spectral Partition.- Mining Databases to Mine Queries Faster.- MACs: Multi-Attribute Co-clusters with High Correlation Information.- Bi-directional Joint Inference for Entity Resolution and Segmentation Using Imperatively-Defined Factor Graphs.-Latent Dirichlet Allocation for Automatic Document Categorization.- New Regularized Algorithms for Transductive Learning.- Enhancing the Performance of Centroid Classifier by ECOC and Model Refinement.- Optimal Online Learning Procedures for Model-Free Policy Evaluation.- Kernels for Periodic Time Series Arising in Astronomy.- K-Subspace Clustering.- Latent Dirichlet Bayesian Co-Clustering.- Variational Graph Embedding for Globally and Locally Consistent Feature Extraction.- Protein Identification from Tandem Mass Spectra with Probabilistic Language Modeling.- Causality Discovery with Additive Disturbances: An Information-Theoretical Perspective.- Subspace Regularization: A New Semi-supervised Learning Method.- Heteroscedastic Probabilistic Linear Discriminant Analysis with Semi-supervised Extension.- Semi-Supervised Multi-Task Regression.- A Flexible and Efficient Algorithm for Regularized Fisher Discriminant Analysis.- Debt Detection in Social Security by Sequence Classification Using Both Positive and Negative Patterns.- Learning the Difference between Partially Observable Dynamical Systems.- Universal Learning over Related Distributions and Adaptive Graph Transduction.- The Feature Importance Ranking Measure.- Demo Papers.- OTTHO: On the Tip of My THOught.- Protecting Sensitive Topics in Text Documents with PROTEXTOR.- Enhanced Web Page Content Visualization with Firefox.- ClusTR: Exploring Multivariate Cluster Correlations and Topic Trends.- Visual OntoBridge: Semi-automatic Semantic Annotation Software.- Semi-automatic Categorization of Videos on VideoLectures.net.- Discovering Patterns in Flows: A Privacy Preserving Approach with the ACSM Prototype.- Using Temporal Language Models for Document Dating.- Omiotis: A Thesaurus-Based Measure of Text Relatedness.- Found in Translation.- A Community-Based Platform for Machine Learning Experimentation.- TeleComVis: Exploring Temporal Communities in Telecom Networks.