Sparse coding, which is the decomposition of a vector using only a few basis elements, is widely used in machine learning and image processing. The basis set, also called dictiona...
Louise Benoit, Julien Mairal, Francis Bach, Jean P...
Machine learning with few training examples always leads to over-fitting problems, whereas human individuals are often able to recognize difficult object categories from only one ...
Abstract. Problem solving with experiences that are recorded in text form requires a mapping from text to structured cases, so that case comparison can provide informed feedback fo...
Nirmalie Wiratunga, Robert Lothian, Sutanu Chakrab...
Computational diagnosis of cancer is a classification problem, and it has two special requirements on a learning algorithm: perfect accuracy and small number of features used in t...
Functional Magnetic Resonance Imaging(fMRI) has enabled scientists to look into the active human brain, leading to a flood of new data, thus encouraging the development of new data...
Lei Zhang 0002, Dimitris Samaras, Dardo Tomasi, Ne...