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...
We analyze the formal grounding behind Negative Correlation (NC) Learning, an ensemble learning technique developed in the evolutionary computation literature. We show that by rem...
We report a method for semi-automated segmentation of extended features such as filamentous structures in electron tomograms. We present an application of this method for the auto...
Sriram Subramaniam, Peijun Zhang, David Germain, T...
A new class of associations (polynomial itemsets and polynomial association rules) is presented which allows for discovering nonlinear relationships between numeric attributes wit...
Long-term search history contains rich information about a user's search preferences. In this paper, we study statistical language modeling based methods to mine contextual i...