Background: Baum-Welch training is an expectation-maximisation algorithm for training the emission and transition probabilities of hidden Markov models in a fully automated way. I...
Abstract. Many computer vision problems such as object segmentation or reconstruction can be formulated in terms of labeling a set of pixels or voxels. In certain scenarios, we may...
We present an approximation method that solves a class of Decentralized hybrid Markov Decision Processes (DEC-HMDPs). These DEC-HMDPs have both discrete and continuous state variab...
Regeneration of biometric templates from match scores has security and privacy implications related to any biometric based authentication system. In this paper, we propose a novel...
We extend the lower bound of Adler et. al [1] and Berenbrink [3] for parallel randomized load balancing algorithms. The setting in these asynchronous and distributed algorithms is...