We investigate Monte Carlo Markov Chain (MCMC) procedures for the random sampling of some one-dimensional lattice paths with constraints, for various constraints. We will see that...
We present a novel boosting algorithm, called SoftBoost, designed for sets of binary labeled examples that are not necessarily separable by convex combinations of base hypotheses....
Manfred K. Warmuth, Karen A. Glocer, Gunnar Rä...
? In this paper we propose an adaptive scheduling and voltage/frequency selection algorithm which targets at energy harvesting systems. The proposed algorithm adjusts the processor...
This paper considers a method that combines ideas from Bayesian learning, Bayesian network inference, and classical hypothesis testing to produce a more reliable and robust test o...
Our goal is to automatically obtain a distributed and fault-tolerant embedded system: distributed because the system must run on a distributed architecture; fault-tolerant because...