Background: During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have...
We propose a new approach to value function approximation which combines linear temporal difference reinforcement learning with subspace identification. In practical applications...
Flow measurement evolved into the primary method for measuring the composition of Internet traffic. Large ISPs and small networks use it to track dominant applications, dominant ...
Binary classification is a core data mining task. For large datasets or real-time applications, desirable classifiers are accurate, fast, and need no parameter tuning. We presen...
Motivation: Genome maps are fundamental to the study of an organism and essential in the process of genome sequencing which in turn provides the ultimate map of the genome. The in...
Thomas Faraut, Simon de Givry, Patrick Chabrier, T...