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...
High quality segmentation of brain MR images is a challenging task. To deal with this problem many automatic segmentation methods rely on atlas information of anatomical structure...
Kilian M. Pohl, W. Eric L. Grimson, Sylvain Bouix,...
We introduce a multi-label classification model and algorithm for labeling heterogeneous networks, where nodes belong to different types and different types have different sets of...
Ralitsa Angelova, Gjergji Kasneci, Fabian M. Sucha...
This paper presents a prediction algorithm for estimating the upper bound of future Web traffic volume. Unlike traditional traffic predictions that are performed at a single time ...
Abstract. Model selection is an important problem in statistics, machine learning, and data mining. In this paper, we investigate the problem of enabling multiple parties to perfor...