Each of the topic areas is expanded below but the sub-topics list is not exhaustive. Papers may address one or more of the listed sub-topics, although authors should not feel limited by them. Unlisted but related sub-topics are also acceptable, provided they fit in one of the following main topic areas:

1. THEORY AND METHODS
2. APPLICATIONS

AREA 1: THEORY AND METHODS

Advanced Learning Methods
Evolutionary Computation
Exact and Approximate Inference
Feature Selection and Extraction
Fuzzy Logic
Graphical and Graph-based Models
Hybrid Learning Algorithms
ICA, PCA, CCA and other Linear Models
Kernel Methods
Knowledge Acquisition and Representation
Learning from Multiple Sources/Methods
Bayesian Models
Matrix Factorization
Missing Data
Model Selection
Neural Networks and Deep Learning
Regression
Similarity and Distance Learning
Sparsity
Stochastic Methods
Case-Based Reasoning
Classification
Clustering
Computational Learning Theory and Optimization
Deep Learning
Embedding and Manifold Learning
Ensemble Methods
AREA 2: APPLICATIONS

Action Recognition
Information Retrieval
Learning in Process Automation and Control
Medical Imaging
Motion and Tracking
Natural Language Processing
Object Recognition/Tracking
Robotics
Sensors and Early Vision
Shape Representation
Signal Processing
Audio and Speech Analysis
Video Analysis
Virtual Environments
Web Applications
Bioinformatics and Systems Biology
Biometrics
Document Analysis
Economics, Business and Forecasting Applications
Image Understanding
Image-based Modelling
Industry Related Applications