Background: The availability of complete genomic sequences for hundreds of organisms promises to make obtaining genome-wide estimates of substitution rates, selective constraints ...
Amy Egan, Anup Mahurkar, Jonathan Crabtree, Jonath...
Representing articulated objects as a graphical model has gained much popularity in recent years, often the root node of the graph describes the global position and orientation of...
This paper investigates the use of the Bayesian inference for devising an unsupervised sketch rendering procedure. As likelihood model of this inference, we exploit the recent sta...
Lasso is a regularization method for parameter estimation in linear models. It optimizes the model parameters with respect to a loss function subject to model complexities. This p...
We give a simple framework which is an alternative to the celebrated and widely used shifting strategy of Hochbaum and Maass [J. ACM, 1985] which has yielded efficient algorithms ...