Sentence examples for preserving embedding from inspiring English sources

neighborhood preserving embedding.

Moreover, some geometrically motivated approaches such as locality preserving projection (LPP) [15] and neighboring preserving embedding (NPE) [16] have been shown effectiveness for face recognition.

In addition, the neighborhood preserving embedding (NPE) (He et al. 2005b) algorithm was put forward to keep the local neighborhood structure on the manifold of the data samples.

In this paper, a novel dimensionality reduction technique, named sparse representation preserving embedding (SRPE), is proposed by utilizing the sparse reconstruction weights and noise-removed data recovered from robust sparse representation.

The neighborhood preserving embedding (NPE) [28], principal component analysis (PCA) [29], maximally collapsing metric learning (MCML) [30], stochastic proximity embedding (SPE) [31] and diffusion maps [32] also have high sensitivity with increased however FP/min.

Here, we report the occurrence of fossil spermatozoa that are preserved embedded in the wall layers of a 50-Myr-old (early Eocene) clitellate cocoon from Antarctica.

"The motivation appears to be liquidation, rather than preserving the embedded knowledge and experience that these artifacts bring," said Kenneth Finkel, lecturer in American studies at Temple University who briefly served as deputy director of the museum.

This paper presents how to use KDM to modernize legacy systems, making them more agile, preserving the embedded business knowledge and reducing maintenance costs.

However, we cannot exclude that other mechanisms play a relevant role in preserving tumor embedded islets, including the release of local immunosuppressive factors, the inability of leukocytes to infiltrate neoplastic tissue and the presence of a generalized immune-compromised state due to the large tumor mass.

With regard to the opportunity to scale in the range [0,1], the features in input to the SVM and the experiments evidenced that non-scaled data better preserved the embedded information: the average correct estimations (taking into account all the possible descriptors and combinations of dataset balancing) were 92.3 % in the case of non-scaled input and 85.4 % in the case of scaled input.

Recently, a variety of other nonlinear embeddings have been proposed, such as locally linear embedding (LLE) (Roweis and Saul, 2000), isomap (Tenenbaum et al., 2000), t-SNE (van der Maaten and Hinton, 2008), tree-preserving embedding (TPE) (Shieh et al., 2011) or autoencoders (Hinton and Salakhutdinov, 2006).