Keywords

Probabilistic Models and Methods:

• Approximate Inference
• Bayesian Nonparametrics
• Gaussian Processes
• Temporal Models and Sequence Data
• Structured and Relational Data
• Model Selection & Structure Learning
• Exact Inference
• Graphical Models
• Missing Data

Supervised Learning:

• Ensemble Methods and Boosting
• Neural Networks
• Kernel Methods
• Large Margin Methods
• Classification
• Regression
• Sparsity and Feature Selection
• Learning with Structured Data

Unsupervised and Semi-supervised Learning:

• Spectral Methods
• Embeddings and Manifold Learning
• Topic Models
• Similarity and Distance Learning
• Matrix Factorization
• Active Learning
• Clustering
• ICA, PCA, CCA & Other Linear Models

Theory:

• Statistical Learning Theory
• Online Learning
• Information Theory
• Game Theory & Computational Economics
• Consistency

Neuroscience:

• Computational Neural Models
• Neural Coding
• Brain Imaging
• Brain-computer Interfaces & Neural Prostheses

Cognitive Science:

• Knowledge Representation & Acquisition
• Reinforcement Learning
• Language
• Response Time Modeling

Applications:

• Natural Language Processing
• Collaborative Filtering
• Bioinformatics
• Information Retrieval
• Ranking
• Web Applications
• Time Series Prediction
• Systems Biology

Vision:

• Object Recognition
• Image Segmentation
• Motion and Tracking
• Visual Features
• Natural Scene Statistics
• Visual Perception

Speech and Signal Processing:

• Audio and Speech Retrieval
• Auditory Perception & Modeling
• Music Modeling & Analysis
• Speech Recognition
• Signal Processing

Optimization:

• Convex Optimization
• Stochastic Methods
• Combinatorial Optimization

Control and Reinforcement Learning

Robotics

Hardware