— We propose an implementable new universal lossy source coding algorithm. The new algorithm utilizes two wellknown tools from statistical physics and computer science: Gibbs sam...
We describe and demonstrate the effectiveness of a method of predicting protein secondary structures, sheet regions in particular, using a class of stochastic tree grammars as rep...
We present a new family of linear time algorithms based on sufficient statistics for string comparison with mismatches under the string kernels framework. Our algorithms improve t...
We derive a family of kernels on dynamical systems by applying the Binet-Cauchy theorem to trajectories of states. Our derivation provides a unifying framework for all kernels on d...
S. V. N. Vishwanathan, Alexander J. Smola, Ren&eac...
Background: Many current gene prediction methods use only one model to represent proteincoding regions in a genome, and so are less likely to predict the location of genes that ha...
Shaun Mahony, James O. McInerney, Terry J. Smith, ...