Both the logic and the stochastic analysis of discrete-state systems are hindered by the combinatorial growth of the state space underlying a high-level model. In this work, we con...
This paper presents improved approximation algorithms for the problem of multiprocessor scheduling under uncertainty (SUU), in which the execution of each job may fail probabilist...
Christopher Y. Crutchfield, Zoran Dzunic, Jeremy T...
Abstract-- This paper describes the stochastic model order reduction algorithm via stochastic Hermite Polynomials from the practical implementation perspective. Comparing with exis...
Yi Zou, Yici Cai, Qiang Zhou, Xianlong Hong, Sheld...
Abstract. The asynchronous techniques that exist within the programming with distributed constraints are characterized by the occurrence of the nogood values during the search for ...
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...