Conference Areas1.

THEORY AND METHODS2.

APPLICATIONSAREA 1: THEORY AND METHODS    Exact and Approximate Inference    Density Estimation    Bayesian Models    Gaussian Processes    Model Selection    Graphical and Graph-based Models    Missing Data    Ensemble Methods    Neural Networks    Kernel Methods    Large Margin Methods    Classification    Regression    Sparsity    Feature Selection and Extraction    Spectral Methods    Embedding and Manifold Learning    Similarity and Distance Learning    Matrix Factorization    Clustering    ICA, PCA, CCA and other Linear Models    Fuzzy Logic    Active Learning    Cost-sensitive Learning    Incremental Learning    On-line Learning    Structured Learning    Multi-agent Learning    Multi-instance Learning    Reinforcement Learning    Instance-based Learning    Knowledge Acquisition and Representation    Meta Learning    Multi-strategy Learning    Case-Based Reasoning    Inductive Learning    Computational Learning Theory    Cooperative Learning    Evolutionary Computation    Information Retrieval and Learning    Hybrid Learning Algorithms    Planning and Learning    Convex Optimization    Stochastic Methods    Combinatorial OptimizationAREA 2: APPLICATIONS    Natural language processing    Information retrieval    Ranking    Web Applications    Economics, Business and Forecasting Applications    Bioinformatics and Systems Biology    Audio and Speech Processing    Signal Processing    Image Understanding    Sensors and Early Vision    Motion and Tracking    Image-based Modelling    Shape Representation    Object Recognition    Video Analysis    Medical Imaging    Learning and Adaptive Control    Perception    Learning in Process Automation    Learning of Action Patterns    Virtual Environments    Robotics