Abstract: In this paper we propose a structured sparse representation based visual tracking algorithm by using both the generative appearance model and the discriminative model. Firstly, structured ...

Abstract: Sparse representation is capable of modeling signals as linear combination of a few atoms from a pre-trained dictionary. It allows learning an adaptive dictionary that leads to highly sparse ...

Sparse data can impact the effectiveness of machine learning models. As students and experts alike experiment with diverse datasets, sparse data poses a challenge. The Leeds Master’s in Business ...

The Annals of Applied Statistics, Vol. 7, No. 2 (June 2013), pp. 799-822 (24 pages) Sparse latent multi-factor models have been used in many exploratory and predictive problems with high-dimensional ...