This brief presents an efficient and scalable online learning algorithm for recurrent neural networks (RNNs). The approach is based on the real-time recurrent learning (RTRL) algor...
In large networks, maintaining precise global network state information is almost impossible. Many factors, such as non-negligible propagation delay, infrequent state updates due ...
Current systems for managing workload on clusters of workstations, particularly those available for Linux-based (Beowulf) clusters, are typically based on traditional process-base...
Daniel Andresen, Nathan Schopf, Ethan Bowker, Timo...
Abstract: We have developed a fitting algorithm able to extract spectral and dynamic properties of a three level oscillator from a two-dimensional infrared spectrum (2D-IR) detecte...
Riccardo Chelli, Victor V. Volkov, Roberto Righini
In this paper we study distributed algorithms on massive graphs where links represent a particular relationship between nodes (for instance, nodes may represent phone numbers and ...
Florent Becker, Adrian Kosowski, Nicolas Nisse, Iv...