The conference calls for high-quality, unpublished, original research papers in the theory and practice of machine learning and pattern recognition. We encourage submissions from all over the world. Topics of interest include but are not limited to:

Machine Learning

▪ Active learning
▪ Dimensionality reduction
▪ Feature selection
▪ Graphical models
▪ Imitation learning
▪ Intelligent Business Computing
▪ Intelligent Systems
▪ Intelligent control system
▪ Intelligent human machine interface
▪ Intelligent robot
▪ Latent variable models
▪ Learning for big data
▪ Learning from noisy supervision
▪ Learning in graphs
▪ Multi-objective learning
▪ Multiple instance learning
▪ Multi-task learning
▪ Online learning
▪ Optimization
▪ Reinforcement learning
▪ Relational learning
▪ Semi-supervised learning
▪ Sparse learning
▪ Statistical machine learning
▪ Structured output learning
▪ Supervised learning
▪ Transfer learning
▪ Unsupervised learning
▪ Other machine learning methodologies

Pattern Recognition

▪ Analysis and detection of singularities
▪ Animation image analysis
▪ Classification
▪ Cluster analysis
▪ Deformation analysis
▪ Descriptor of shapes
▪ Diagnosis of faults
▪ Document analysis
▪ Emotion computation
▪ Enhancement and restoration
▪ Feature extraction
▪ Hand gestures classification
▪ Human face recognition
▪ Image compression
▪ Image fusion
▪ Image indexing and retrieval
▪ Image recovery
▪ Invariant representation of patterns
▪ Iris pattern recognition
▪ Learning theory
▪ Machine vision
▪ Medical image analysis
▪ Noise reduction
▪ Nonstationary stochastic processing
▪ Range imaging and detection
▪ Segmentation
▪ Stochastic pattern recognition
▪ Texture analysis and classification
▪ Visualization