Sparse coding--that is, modelling data vectors as sparse linear combinations of basis elements--is widely used in machine learning, neuroscience, signal processing, and statistics...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
A new class of associations (polynomial itemsets and polynomial association rules) is presented which allows for discovering nonlinear relationships between numeric attributes wit...
In this paper, we present a novel content-based image error detection and error concealment algorithm to improve the image quality degraded during its transmission over wireless c...
In complex distributed applications, a problem is often decomposed into a set of subproblems that are distributed to multiple agents. We formulate this class of problems with a tw...
We describe a Markov chain Bayesian classification tool, SCS, that can perform data-driven classification of proteins and protein segments. Training data for interesting classific...
Timothy Meekhof, Gary W. Daughdrill, Robert B. Hec...