Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Abstract— This paper proposes a simulation-based active policy learning algorithm for finite-horizon, partially-observed sequential decision processes. The algorithm is tested i...
Ruben Martinez-Cantin, Nando de Freitas, Arnaud Do...
In many applications, we monitor data obtained from multiple streaming sources for collective decision making. The task presents several challenges. First, data in sensor networks...
Recommender systems — systems that suggest to users in e-commerce sites items that might interest them — adopt a static view of the recommendation process and treat it as a pr...
In the 21st century, the Biotechnology industry has the potential to inspire a number of management tools and theories, just as the Automobile industry did in the 20th century. Th...