In this paper we discuss boosting algorithms that maximize the soft margin of the produced linear combination of base hypotheses. LPBoost is the most straightforward boosting algor...
Manfred K. Warmuth, Karen A. Glocer, S. V. N. Vish...
In this paper, a novel feature selection algorithm for object tracking is proposed. This algorithm performs more robust than the previous works by taking the correlation between f...
In numerous applications of image processing, e.g. astronomical and medical imaging, data-noise is well-modeled by a Poisson distribution. This motivates the use of the negative-lo...
We present a new approach to preconditioning for very large, sparse, non-symmetric, linear systems. We explicitly compute an approximate inverse to our original matrix that can be...
This work focuses on several optimization problems involved in recovery of sparse solutions of linear inverse problems. Such problems appear in many fields including image and sig...