This paper proposes the incremental Bayesian optimization algorithm (iBOA), which modifies standard BOA by removing the population of solutions and using incremental updates of t...
This paper proposes a nonparametric Bayesian method for exploratory data analysis and feature construction in continuous time series. Our method focuses on understanding shared fe...
We developed a model based on nonparametric Bayesian modeling for automatic discovery of semantic relationships between words taken from a corpus. It is aimed at discovering seman...
The automated detection and tracking of humans in computer vision necessitates improved modeling of the human skin appearance. In this paper we propose a Bayesian network approach...
Ira Cohen, Nicu Sebe, Theo Gevers, Thomas S. Huang
We use graphical models and structure learning to explore how people learn policies in sequential decision making tasks. Studies of sequential decision-making in humans frequently...