Reassembly of fragmented objects from a collection of randomly mixed fragments is a common problem in classical forensics. In this paper we address the digital forensic equivalent...
We present a novel discriminative training algorithm for n-gram language models for use in large vocabulary continuous speech recognition. The algorithm uses large margin estimati...
Abstract. We present a Bayesian treatment of non-negative matrix factorization (NMF), based on a normal likelihood and exponential priors, and derive an efficient Gibbs sampler to ...
A commonly used tool in disease association studies is the search for discrepancies between the haplotype distribution in the case and control populations. In order to find this d...
First-order Markov models have been successfully applied to many problems, for example in modeling sequential data using Markov chains, and modeling control problems using the Mar...