Memory-based collaborative filtering is the most popular approach to build recommender systems. Despite its success in many applications, it still suffers from several major limitations, including data sparsity. Sparse data affect the quality of the user similarity measurement and consequently the quality of the recommender system. In this paper, we propose a novel user similarity measure based...

Background: DNA microarray is a useful technology that simultaneously assesses the expression of thousands of genes. It can be utilized for the detection of cancer types and cancer biomarkers. This study aimed to predict blood cancer using leukemia gene expression data and a robust ℓ2,p-norm sparsity-based gene selection method. Materials and Methods: In this descriptive study, the microarray ...

Sparse stealth attack constructions that minimize the mutual information between state variables and observations are proposed. The construction is formulated as design of a multivariate Gaussian distribution aims to while limiting Kullback-Leibler divergence under without attack. sparsity constraint incorporated support distribution. Two heuristic greedy algorithms for first algorithm assumes ...

this study deals with the 3d recovering of magnetic susceptibility model by incorporating the sparsity-based constraints in the inversion algorithm. for this purpose, the area under prospect was divided into a large number of rectangular prisms in a mesh with unknown susceptibilities. tikhonov cost functions with two sparsity functions were used to recover the smooth parts as well as the sharp ...

We analyse the one-loop fermionic contribution for the scalar effective potential in the temperature dependent Yukawa model. In order to regularize the model a mix between dimensional and analytic regularization procedures is used. We find a general expression for the fermionic contribution in arbitrary spacetime dimension. It is found that in D = 3 this contribution is finite.