Consider the decomposition of a signal into features that undergo transformations drawn from a continuous family. Current methods discretely sample the transformations and apply s...
Chaitanya Ekanadham, Daniel Tranchina, Eero P. Sim...
Nonparametric methods are widely applicable to statistical learning problems, since they rely on a few modeling assumptions. In this context, the fresh look advocated here permeat...
—An expression can be approximated by a sequence of temporal segments called neutral, onset, offset and apex. However, it is not easy to accurately detect such temporal segments ...
We review the history of modeling score distributions, focusing on the mixture of normal-exponential by investigating the theoretical as well as the empirical evidence supporting i...
Over the last decade the cost of producing genomic sequences has dropped dramatically due to the current so called “next-gen” sequencing methods. However, these next-gen seque...