Maximum variance unfolding (MVU) is an effective heuristic for dimensionality reduction. It produces a low-dimensional representation of the data by maximizing the variance of the...
Le Song, Alex J. Smola, Karsten M. Borgwardt, Arth...
Point matching is the task of finding a set of correspondences between two sets of points under some geometric transformation. A local search algorithm for point matching is pres...
Linear and affine subspaces are commonly used to describe appearance of objects under different lighting, viewpoint, articulation, and identity. A natural problem arising from the...
Eigenvalue problems are rampant in machine learning and statistics and appear in the context of classification, dimensionality reduction, etc. In this paper, we consider a cardina...
Bharath K. Sriperumbudur, David A. Torres, Gert R....
This paper presents an efficient computational method to identify a local symmetry axis in 3-dimensional viral structures obtained using electron cryomicroscopy. Local symmetry is...