Keywords

Keywords have to be chosen during the paper submission process. The purpose of the keywords is to assist the assignment of papers to area chairs and reviewers. They are sorted roughly according to popularity.

Deep Learning or Neural Networks
Large Scale Learning and Big Data
Convex Optimization
Clustering
Learning Theory
Graphical Models
Online Learning
Sparsity and Feature Selection
Reinforcement Learning Algorithms
Kernel Methods
Matrix Factorization
Bandit Algorithms
Component Analysis (ICA,PCA,CCA, FLDA)
Stochastic Methods
Gaussian Processes
MCMC
Nonlinear Dimension Reduction and Manifold Learning
Time Series Analysis
Model Selection and Structure Learning
Multi-task and Transfer Learning
Bayesian Nonparametrics
Spectral Methods
Variational Inference
Combinatorial Optimization
Semi-Supervised Learning
Structured Prediction
Ensemble Methods and Boosting
Graph-based Learning
Active Learning
Ranking and Preference Learning
Similarity and Distance Learning
Information Theory
Game Theory and Econometrics
Regularization and Large Margin Methods
Causality
(Application) Object and Pattern Recognition
(Application) Computer Vision
(Application) Natural Language and Text Processing
(Application) Signal and Speech Processing
(Application) Social Networks
(Application) Information Retrieval
(Application) Web Applications and Internet Data
(Application) Collaborative Filtering and Recommender Systems
(Application) Privacy, Anonymity, and Security
(Application) Bioinformatics and Systems Biology
(Cognitive/Neuroscience) Perception
(Cognitive/Neuroscience) Neural Coding
(Cognitive/Neuroscience) Theoretical Neuroscience
(Cognitive/Neuroscience) Reinforcement Learning
(Cognitive/Neuroscience) Language
(Other) Classification
(Other) Regression
(Other) Optimization
(Other) Probabilistic Models and Methods
(Other) Machine Learning Topics
(Other) Unsupervised Learning Methods
(Other) Applications
(Other) Cognitive Science
(Other) Bayesian Inference
(Other) Neuroscience
(Other) Statistics
(Other) Robotics and Control