Sentence examples for sparse models and from inspiring English sources

These techniques can yield sparse models and hence perform simultaneous variable selection and estimation.

When the outcome is survival time, the objective function is usually written based on hazards at the failure time and posing penalties on the coefficients can yield sparse models and hence perform simultaneous variable selection and estimation.

Motivated by the recent advances in the use of CS in MRI and ℓ0-minimization, we propose rank-one and transformed sparse models and algorithms to significantly accelerate dynamic MRI.

Such penalties, developed and studied extensively over the past two decades, are known to encourage sparse models and are particularly useful in contexts (such as the current one) in which a relatively small number of variables (i.e., genes) need to be selected from among a very large number.

In Section 3 we review the different sparse modeling and optimization criteria.

It works on the linear dynamic sparse model and meets the sparsity constraint.

The proposed reconstruction method is composed of two collaborative processes which are derived from two nonlocal self-similarity models: the jointly sparse model and the autoregressive model.

Outline: The paper is organised as follows: Section 2 contains the complete problem setup, explaining the combined low-rank and sparse model and as well as the corruption model.

A uniform elemental power constraint is adopted as the optimization criterion is to minimize the mutual coherence of the sensing matrix using a sparse model and to achieve high-resolution estimation in both range and angle dimensions.

This formulation makes clear the dependence of the IAM ℳ on the underlying scene x: ℳ = ℳ x) = {R θ x: θ ∈ Θ} ⊂ ℝ N. Supposing we believe x to obey a sparse model and supposing the camera positions are known, this formulation also facilitates a joint recovery program that can ensure global consistency while exploiting the structure of the underlying scene.

Before introducing the improved sparse model, we first review the sparse model and show how to apply it on M-FISH image data analysis.