InhaltsangabeDeclarative Modeling for Machine Learning and Data Mining.- Recent Developments in Pattern Mining.- Exploring Sequential Data.- Large Scale Spectral Clustering Using Resistance Distance and SpielmanTeng Solvers. Prediction of Quantiles by Statistical Learning and Application to GDP Forecasting.- Policy Search in a Space of Simple Closed-form Formulas: Towards Interpretability of Reinforcement Learning.- Towards Finding Relational Redescriptions.- Descriptive Modeling of Systemic Banking Crises.- A Trim Distance between Positions in Nucleotide Sequences.- Data Squashing for HSV Subimages by an Autonomous Mobile Robot. Cohesive Coevolution Patterns in Dynamic Attributed Graphs. Efficient Redundancy Reduced Subgroup Discovery via Quadratic Programming. HCAC: Semisupervised Hierarchical Clustering Using Confidence Based Active Learning.- LF-CARS: A Loose Fragment-Based Consensus Clustering Algorithm with a Robust Similarity.- Fast Approximation Algorithm for the 1-Median Problem.- Online Co-regularized Algorithms.- Fast Progressive Training of Mixture Models for Model Selection.- Including Spatial Relations and Scales within Sequential Pattern Extraction. Predicting Ramp Events with a StreamBased HMM Framework. Burst Detection in a Sequence of Tweets Based on Information Diffusion Model.- Error-Correcting Output Codes as a Transformation from Multi-Class to MultiLabel Prediction. An Assessment on Loan Performance from Combined Quantitative and Qualitative Data in XML.- Structural Change Pattern Mining Based on Constrained Maximal kPlex Search. Enhancing Patent Expertise through Automatic Matching with Scientific Papers.- Soft Threshold Constraints for Pattern Mining.