Algorithms for learning the conditional probabilities of Bayesian networks with hidden variables typically operate within a high-dimensional search space and yield only locally op...
It is well-known that the eigenvalue spectrum of the Laplacian matrix of a network contains valuable information about the network structure and the behavior of many dynamical proc...
Victor M. Preciado, Michael M. Zavlanos, Ali Jadba...
Online adaptation is a key requirement for image processing applications when used in dynamic environments. In contrast to batch learning, where retraining is required each time a...
In this paper we explore the use of several types of structural restrictions within algorithms for learning Bayesian networks. These restrictions may codify expert knowledge in a g...
Abstract—We propose a novel algorithm for detecting wormhole attacks in wireless multi-hop networks. The algorithm uses only connectivity information to look for forbidden substr...