Prediction: Machine Learning and Statistics
The Catch-Up Phenomenon in Bayesian Inference
Introduction to Probability and Statistics
Modeling reality without sacrificing data: Inferentially tractable models for complex social systems
Deep Belief Networks
A Flexible Model for Count Data: The COM-Poisson Distribution
Machine Learning
Gaussian Process Temporal Difference
Entropy-based Variational Scheme for Fast Bayes Learning of Gaussian Mixture
The KL-UCB Algorithm for Bounded Stochastic Bandits and Beyond