We propose to use the sparseness property of the gradient probability distribution to estimate the intensity nonuniformity in medical images, resulting in two novel automatic metho...
Yuanjie Zheng, Murray Grossman, Suyash P. Awate,...
Abstract. We present new performance models and a new, more compact data structure for cache blocking when applied to the sparse matrixvector multiply (SpM×V) operation, y ← y +...
Rajesh Nishtala, Richard W. Vuduc, James Demmel, K...
In this paper we present a simple hierarchical Bayesian treatment of the sparse kernel logistic regression (KLR) model based MacKay's evidence approximation. The model is re-p...
In this paper, following the Compressed Sensing (CS) paradigm, we study the problem of recovering sparse or compressible signals from uniformly quantized measurements. We present ...
— In cognitive radio, spectrum sensing is a key component to detect spectrum holes (i.e., channels not used by any primary users). Collaborative spectrum sensing among the cognit...