Keywords
Methodologies and Learning Paradigms
active learning
approximate inference
asymptotics, consistency
Bayesian methods
Bayesian nonparametrics
boosting
causality
clustering
computational learning theory
deep learning
discrete optimization
ensemble methods
feature selection
game theory and mechanism design
Gaussian processes
graphical models
information theory
kernel methods
large margin methods
large scale learning
matrix and tensor factorization
model selection
Monte Carlo methods
nonlinear embedding and manifold learning
online learning
optimization
reinforcement learning and control
semi-supervised learning
sparse estimation, compressed sensing
spectral methods
statistical learning theory
structured prediction
Application Areas
computational biology and genomics
computational neuroscience, cognitive modelling
computer vision
information systems, web processing
robotics, human-computer interaction
scientific data analysis
social and information networks
speech