Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a particular linear combination of the input variables while constraining the numb...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
Many applications of supervised learning require good generalization from limited labeled data. In the Bayesian setting, we can try to achieve this goal by using an informative pr...
We propose a new global registration method for estimating the cardiac displacement field in 2D sequences of ultrasound images of the heart. The basic idea is to select a referenc...
This paper develops an energy minimization algorithm to reconstruct the 3D motion of transplanted hearts of small animals (rats) from tagged magnetic resonance (MR) sequences. We ...
We present an efficient algorithm for nonlocal image filtering with applications in electron cryomicroscopy. Our denoising algorithm is a rewriting of the recently proposed nonloc...