This paper proposes a method of finding a discriminative linear transformation that enhances the data's degree of conformance to the compactness hypothesis and its inverse. Th...
Linear Discriminant Analysis (LDA) is one of the most popular approaches for feature extraction and dimension reduction to overcome the curse of the dimensionality of the high-dime...
We propose a max-margin formulation for the multi-label classification problem where the goal is to tag a data point with a set of pre-specified labels. Given a set of L labels, a...
Bharath Hariharan, Lihi Zelnik-Manor, S. V. N. Vis...
Abstract. Taxonomy provides one of the most powerful ways to navigate sequence data bases but currently, users are forced to formulate queries according to a single taxonomic class...
Linear techniques are widely used to reduce the dimension of image representation spaces in applications such as image indexing and object recognition. Optimal Component Analysis ...
Yiming Wu, Xiuwen Liu, Washington Mio, Kyle A. Gal...