Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
With the rise in popularity of compatible finite element, finite difference and finite volume discretizations for the time domain eddy current equations, there has been a correspon...
Pavel B. Bochev, Jonathan J. Hu, Christopher M. Si...
We introduce a new method for data clustering based on a particular Gaussian mixture model (GMM). Each cluster of data, modeled as a GMM into an input space, is interpreted as a hy...
Abstract--Sparse representations of signals have drawn considerable interest in recent years. The assumption that natural signals, such as images, admit a sparse decomposition over...
This paper tackles the problem of the computation of a planar polygonal curve from a digital planar curve, such that the digital data can be exactly retrieved from the polygonal c...