Gaussian Process (GP) models are a class of flexible non-parametric mode...
In this paper, we propose a Spatial Robust Mixture Regression model to
i...
Human beings learn causal models and constantly use them to transfer
kno...
This paper studies the problem of globally optimizing a variable of inte...
We study adaptive importance sampling (AIS) as an online learning proble...
We introduce inference trees (ITs), a new class of inference methods tha...
Hamiltonian Monte Carlo (HMC) is a popular Markov chain Monte Carlo (MCM...
We tackle the problem of collaborative filtering (CF) with side informat...