We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
We consider the exploration/exploitation problem in reinforcement learning (RL). The Bayesian approach to model-based RL offers an elegant solution to this problem, by considering...
A recently proposed Bayesian multiscale tool for exploratory analysis of time series data is reconsidered and umerous important improvements are suggested. The improvements are in...
We propose a simple and practical probabilistic comparison-based model, employing multiple incomplete test concepts, for handling fault location in distributed systems using a Bay...
Yu Lo Cyrus Chang, Leslie C. Lander, Horng-Shing L...
Design of an anisotropic diffusion-based filter that performs Bayesian classification for automatic selection of a proper weight for fairing polygon meshes is proposed. The data a...
Chun-Yen Chen, Kuo-Young Cheng, Hong-Yuan Mark Lia...