We propose an unbounded-depth, hierarchical, Bayesian nonparametric model for discrete sequence data. This model can be estimated from a single training sequence, yet shares stati...
We consider the problem of characterisation of sequences of heterogeneous symbolic data that arise from a common underlying temporal pattern. The data, which are subject to impreci...
A key challenge in applying kernel-based methods for discriminative learning is to identify a suitable kernel given a problem domain. Many methods instead transform the input data...
This paper introduces the first integrated algorithm designed to discover novel motifs in heterogeneous sequence data, which is comprised of coregulated genes from a single genome...
The advent of high-throughput sequencing (HTS) technologies is enabling sequencing of human genomes at a significantly lower cost. The availability of these genomes is hoped to en...