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ICML
2009
IEEE
14 years 9 months ago
A stochastic memoizer for sequence data
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...
Frank Wood, Cédric Archambeau, Jan Gasthaus...
SOFTWARE
2002
13 years 8 months ago
Temporal Probabilistic Concepts from Heterogeneous Data Sequences
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...
Sally I. McClean, Bryan W. Scotney, Fiona Palmer
IJCAI
2007
13 years 10 months ago
Parametric Kernels for Sequence Data Analysis
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...
Young-In Shin, Donald S. Fussell
PSB
2004
13 years 10 months ago
Motif Discovery in Heterogeneous Sequence 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...
Amol Prakash, Mathieu Blanchette, Saurabh Sinha, M...
BIB
2010
68views more  BIB 2010»
13 years 9 months ago
Genome variation discovery with high-throughput sequencing data
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...
Adrian V. Dalca, Michael Brudno