This paper presents three novel Moving Horizon Estimation (MHE) methods for discrete-time partitioned linear systems, i.e. systems decomposed into coupled subsystems with non-over...
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
Multi-agent systems are well suited for building large software systems. A great deal of these complex systems includes process flows that are concerned with time or are even time...
Lars Braubach, Alexander Pokahr, Winfried Lamersdo...
Hash table is used as one of the fundamental modules in several network processing algorithms and applications such as route lookup, packet classification, per-flow state manage...
Haoyu Song, Sarang Dharmapurikar, Jonathan S. Turn...
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...