A clustering framework within the sparse modeling and dictionary learning setting is introduced in this work. Instead of searching for the set of centroid that best fit the data, ...
Pablo Sprechmann, Ignacio Ramirez, Guillermo Sapir...
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
We characterize the performance and power attributes of the conjugate gradient (CG) sparse solver which is widely used in scientific applications. We use cycle-accurate simulatio...
Konrad Malkowski, Ingyu Lee, Padma Raghavan, Mary ...
In this paper we present a novel approach to describe sound mixtures which is based on a geometric viewpoint. In this approach we extend the idea of a nearest-neighbor representat...
— We consider memory subsystem optimizations for improving the performance of sparse scientific computation while reducing the power consumed by the CPU and memory. We first co...