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Aleksandr Y. Aravkin

2 accepted papers

2016

Beyond L2-loss functions for learning sparse models

ICASSP 2016accepted

In sparse learning, the squared Euclidean distance is a popular choice for measuring the approximation quality. However, the use of other forms of parametrized loss functions, including asymmetric losses, has generated research interest. In this paper, we perform sparse learning using a broad class…

Cited by 0SourceScholar
2015

Adaptive As-Natural-As-Possible Image Stitching

CVPR 2015poster

The goal of image stitching is to create natural-looking mosaics free of artifacts that may occur due to relative camera motion, illumination changes, and optical aberrations. In this paper, we propose a novel stitching method, that uses a smooth stitching field over the entire target image, while a…

Cited by 443SourcePDFScholar