Sentence examples for matrix factorization problem from inspiring English sources

The identification of clusters is cast as a Boolean matrix factorization problem over the interaction matrix between trans-factors and mRNAs.

Designing consensus protocols can be viewed as a matrix factorization problem.

For connected undirected graphs, we propose a learning method for solving such matrix factorization problem in a distributed way.

In this section, we will introduce the matrix factorization problem and its connection with the linear unmixing explained above.

Briefly, the problem can be transferred into a matrix factorization problem in Eq. (3) and we adopted the state-of-the-art online dictionary learning algorithm [29] for the sparse representation of the whole-brain fMRI signals.

Similar to [ 29, 30], we adopted the multiplicative update rule [ 31] to estimate H, which was widely accepted as a useful algorithm in solving nonnegative matrix factorization problem.

Although the calculations performed in the Bayesian approach may be modelled as matrix factorization problems, the use of a probabilistic framework may allow not only a more meaningful interpretation of both the results and the hypothesis over which the system is built on, but also the use of an important set of tools and algorithms, as seen above.

When the sources and the mixing matrix are restricted to be non-negative, the problem can be seen as a non-negative matrix factorization (NMF) problem for which many algorithms have been developed[15].

Matrix factorization is the problem of decomposing the input matrix into two or more matrices called factors, such that the product of these factors is close to the input matrix.

However, in the Big Data literature [24, 43], as opposed to low-rank approximation, the community liberally calls this problem a "matrix factorization" as it determines the factors for the input matrix, leading to an overlap between low-rank approximations and matrix factorization techniques.

Various updating techniques based on matrix factorization for different kinds of problems exist in the literature [3, 11, 13, 19 22].