Image restoration problems are often converted into large-scale, nonsmooth and nonconvex optimization problems. Most existing minimization methods are not efficient for solving su...
L1 regularized logistic regression is now a workhorse of machine learning: it is widely used for many classification problems, particularly ones with many features. L1 regularized...
Su-In Lee, Honglak Lee, Pieter Abbeel, Andrew Y. N...
Camera networks have gained increased importance in
recent years. Previous approaches mostly used point correspondences
between different camera views to calibrate
such systems....
We investigate in this article the rigid registration of large sets of points, generally sampled from surfaces. We formulate this problem as a general Maximum-Likelihood (ML) estim...
Standard methods for image interpolation are based on smoothly fitting the image intensity surface. Recent edgedirected interpolation methods add limited geometric information (ed...