Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
Pascal Poupart, Nikos A. Vlassis, Jesse Hoey, Kevi...
Data integrated from multiple sources may contain inconsistencies that violate integrity constraints. The constraint repair problem attempts to find "low cost" changes t...
Philip Bohannon, Michael Flaster, Wenfei Fan, Raje...
Optimal index assignment of multiple description lattice vector quantizer (MDLVQ) can be posed as a large-scale linear assignment problem. But is this expensive algorithmic approa...
Abstract. We investigate the computational complexity of a new combinatorial problem of inferring a smallest possible multi-labeled phylogenetic tree (MUL tree) which is consistent...
Multiprocessor scheduling problems are hard because of the numerous constraints on valid schedules to take into account. This paper presents new schedule representations in order ...
Matthieu Lemerre, Vincent David, Christophe Aussag...