Assembling software components into an architecture is a difficult task because of its combinatorial complexity. There is thus a need for automating this building process, either t...
Nicolas Desnos, Sylvain Vauttier, Christelle Urtad...
Optimized locally exhaustive test pattern generators based on linear sums promise a low overhead, but have an irregular structure. The paper presents a new algorithm able to compu...
Approximate dynamic programming is emerging as a powerful tool for certain classes of multistage stochastic, dynamic problems that arise in operations research. It has been applie...
Bayesian inference is an appealing approach for leveraging prior knowledge in reinforcement learning (RL). In this paper we describe an algorithm for discovering different classes...
Abstract— Many techniques for constructing unitary spacetime constellations have been proposed. To minimize bit-error rate (BER) in a wireless communication system, constellation...