Sentence examples for data regularization from inspiring English sources

The recommendations for this algorithm include early stopping, reweighting used to adjust the sample data, regularization, step size.

where the terms from left are defined as follows: super-resolution or data, regularization potential, and fidelity, respectively.

To training classifiers, they employ Stochastic Gradient Descent [9] with early stopping, reweighting data, regularization, step size and the computation of dot product is parallelized on 16 cores of their computer.

In order to allow Cytoscape users to conveniently apply linear and non-linear dimension reduction methods accompanied by network-based data regularization, we have developed DeDaL, a Cytoscape 3 app for computing and mixing data-driven and structure-driven network layouts.

Imaging scattering has some challenges and it has been stated that the cw method lacks the capability of separating absorption from scattering in the DOT image reconstruction [ 17, 44], but it has been shown that preconditioning of data, regularization and use of multispectral information can separate absorption from scattering coefficient [ 16] and result in good image reconstructions.

However, with too deep an architecture, this loss function yields overfitting, suggesting the need for more data and/or regularization.

This paper proposes a two-dimensional regularized locality preserving projection (2DRLPP) algorithm for feature extraction, which combines locality preserving projection (LPP) method with data roughness regularization.

We explain this effect by observing that, near these data, viscous regularization is non-uniform as the viscosity tends to zero.

To compensate for the slow drift of the electro-hydraulic valves during the warm-up period of the transmission, an adaptive feedforward strategy is implemented with the Dasgupta-Huang Outer Bounding Ellipsoid (DHOBE); because of highly correlated input data, a regularization procedure is added, giving the rDHOBE.

Then starting from the initialized reference model dν estimated from fused MEEG data, MEM regularization was used to find a solution from SNR-transformed concatenated MEEG data, as illustrated in Fig.  2.

We can observe that the model predictions are less sensitive to the error in the data when regularization is applied, i.e. the variance of the model predictions are smaller.