Sensor-based statistical models promise to support a variety of advances in human-computer interaction, but building applications that use them is currently difficult and potentia...
Background: With the rapid expansion of DNA sequencing databases, it is now feasible to identify relevant information from prior sequencing projects and completed genomes and appl...
Learning to predict rare events from sequences of events with categorical features is an important, real-world, problem that existing statistical and machine learning methods are ...
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in the framework of sy...
Sylvain Gelly, Olivier Teytaud, Nicolas Bredeche, ...
In this paper, we improve the performance of intra prediction and simplify mode decision procedure at the same time. For these works, we apply a statistical learning method such a...