sparsity

It discusses the exploitation of sparsity in large LP problems as used in practice.

对高阶线性规划问题实际应用的稀疏技术的开发作了探讨.

This is not only because of the sparsity of the fringed.

这不仅是由于条纹稀疏.

High-dimensional data mining faces the challenges of distributed data sparsity and overlapping feature subspace.

高维数据的挖掘面临着数据分布的稀疏性和特征空间的相交性所带来的挑战.

It is necessary and possible to lead the concept of sparsity into of labor value.

将稀少性的概念引入劳动价值论既有必要,也有可能.

Traditional feature selection algorithms trends to break down in high dimensional Web spaces because of the ( inherent) sparsity of the data object.

传统特征选择算法在多维Web数据中由于其数据对象自身固有的稀缺性而常常失效。

We tackle the sparsity problem in two ways-by feature augmentation and switched method.

我们采用了两种方法来提高数据稀疏时预测的准确性,即属于特征递增型的PearAftersvd方法和属于转换型的LCM_STI方法.

In an application where the sparsity of target impulse response varies with the environment, the performance of proportionate adaptive algorithms is not guaranteed.

系数比例自适应算法主要对稀疏冲激响应有效，在目标冲激响应的稀疏程度随环境变化的应用中，算法的性能不能保证。

As a special type of signal, image signal itself or its semantic meaning has sparsity, which makes it possible to introduce the sparse representation technique to the area of image processing.

作为一种特殊的信号，图像信号本身及其所反映的语义在很多时候具备稀疏性这一特点，这使得稀疏表示相关的理论可以被引入到图像处理这一领域中。

Based on the relation between sparsity and lk norm, a regularization method is presented for the sparse representation of signals.

本文基于lk范数与稀疏性之间的关系，提出了一种基于lk范数的正则化方法，该方法在抑制信号噪声的同时，实现了信息的高精度稀疏表示。

This paper proposes a method of digital literature image compression based on sparsity and synchronization.

提出基于稀疏性与同步性的数字文献图像压缩方法.

By using the augmented state matrix of the linearized power system model and performing the corresponding sparsity-oriented calculation, the correction equation is solved exactly, and the speed of convergence for the selected Ritz values is asymptotically quadratic.

算法中使用了电力系统线性化模型中的增广状态矩阵进行相应面向稀疏的计算，可准确求解修正方程，以保证算法具有渐进二次收敛速度。

Sparsity representation model of permuted alias image is obtained by its mathematical model.

首先，根据这类置换混叠图像的数学模型，得到其稀疏表示的模型。

In machine learning, the sparsity of hypothesis functions is expected to improve the generalization performance and the test speed. Moreover the sparse signal reconstruction is a crucial problem in compressed sensing ( CS).

在机器学习中假设函数的稀疏性对检验速度和推广性能是至关重要的，而稀疏信号的重构在压缩感知中也扮演着举足轻重的作用。

Data set size, dimensionality and sparsity have been identified as aspects that make cluster more difficult.

数据集合的大小, 数据的维数和数据的稀疏性都是制约聚类的不同方面.

Many previous works have applied transfer learning to recommender systems to solve the cold start and rating sparsity problems. Most of these applications transfer user-item rating patterns. However, these applications require that the rating data on the auxiliary domain should be dense enough.

之前也有很多研究将迁移学习应用到推荐系统中来改进推荐系统，但是之前的研究都是迁移推荐系统中的用户评分矩阵，而且这些研究工作都要求源领域中的评分数据足够密集。

Translation template can solve the problem of data sparsity, large storage space and low matching precision of examples.

利用翻译模板可以有效的解决翻译实例的数据稀疏问题、简化实例库的规模并提高实例匹配的精确率。