Model programs represent transition systems that are used fy expected behavior of systems at a high level of abstraction. The main application area is application-level network pro...
High-dimensional statistical inference deals with models in which the the number of parameters p is comparable to or larger than the sample size n. Since it is usually impossible ...
Sahand Negahban, Pradeep Ravikumar, Martin J. Wain...
We present an algorithm which provides the one-dimensional subspace where the Bayes error is minimized for the C class problem with homoscedastic Gaussian distributions. Our main ...
We consider the problem of fitting linearly parameterized models, that arises in many computer vision problems such as road scene analysis. Data extracted from images usually cont...
: The Internet makes it easy to offer large assortments of products, tempting managers to chase the “long tail”—that is, the phenomenon in which niche products gain a signifi...