Sentence examples for manifold learning technique from inspiring English sources

To avoid such deficiencies, a manifold learning technique named maximum variance unfolding (MVU) is considered as an alternative.

This paper proposes a new study to explore the wavelet packet energy (WPE) flow characteristics of vibration signals by using the manifold learning technique.

Locally linear embedding (LLE), as a representative manifold learning technique, is a nonlinear dimension reduction method by mapping the high-dimensional data to a lower dimensional space while preserving the essential properties of the raw data.

Figure 5 Constructing contour trees using manifold learning techniques [[16]].

I will outline how to use manifold learning techniques to capture the functional connectivity architecture in individuals.

Among them, SLLE has become one of the most promising supervised manifold learning techniques due to its simple implementation, and successfully applied for facial expression recognition [28].

However, when there are face images of multiple individuals with varying pose angles, manifold learning techniques often do not give accurate results.

Since this relative arrangement will typically reflect the relative arrangement of the values {θ j } in Θ, we may apply to the compressive measurementsd any number of "manifold learning" techniques (such as ISOMAP [11]) that are designed to discover such parameterizations from unlabeled data.

In order to discover configurations that involve more than four-body interactions described above, we applied non-linear graph manifold learning techniques.

To distinguish between two trajectories, we introduce a novel dissimilarity measure combined with a manifold learned tuning technique to capture the pairwise relationship between the two trajectories.

Many such methods fall under the umbrella of manifold learning, which is a technique meant to take advantage of cases where the data lie on a non-linear subspace that can be represented by a significantly smaller number of dimensions [103].