In this paper, we propose a Bayesian Pursuit algorithm for sparse representation. It uses both the simplicity of the pursuit algorithms and optimal Bayesian framework to determine...
Hadi Zayyani, Massoud Babaie-Zadeh, Christian Jutt...
Sparse signal recovery algorithms utilizing multiple measurement vectors (MMVs) are known to have better performance compared to the single measurement vector case. However, curre...
Point processes are difficult to analyze because they provide only a sparse and noisy observation of the intensity function driving the process. Gaussian Processes offer an attrac...
John P. Cunningham, Krishna V. Shenoy, Maneesh Sah...
The paper presents a novel feature extraction technique for face recognition which uses sparse projection axes to compute a lowdimensional representation of face images. The propos...
In this paper, we propose a bilevel sparse coding model for coupled feature spaces, where we aim to learn dictionaries for sparse modeling in both spaces while enforcing some desi...