Sentence examples for manifold alignment and from inspiring English sources

The results showed the proposed method performed the best followed by manifold regularization, correspondence-based manifold alignment, and CCA being the worst performing in this case.

The proposed method was compared with Canonical Correlation Analysis (CCA) [45], correspondence-based manifold alignment [43], and manifold regularization [44] (target only).

This method uses a manifold alignment based approach and is an extension from their previous framework [43].

This manifold alignment term contains three parts: geometric, similarity, and dissimilarity terms.

Wang and Mahadevan [27] proposed an HDA solution called Domain Adaption using Manifold Alignment (DAMA).

The effectiveness of the semi-supervised manifold alignment methods may be very limited with very limited prior information.

In this paper, we propose a novel semi-supervised manifold alignment algorithm with few given pairwise correspondences.

The algorithm by Wang [121], referred to as the domain adaptation manifold alignment (DAMA) algorithm, proposes using a manifold alignment [45] process to perform a symmetric transformation of the domain input spaces.

Along with the aforementioned metric, a manifold alignment term based on label information is also introduced into the objective function.

Standard manifold alignment techniques require a small amount of cross-domain correspondence relationships to learn mapping functions, but these correspondences are often difficult to obtain and sometimes require manual translation which can be highly expensive.

In recent years, manifold alignment methods have aroused a great of interest in the machine learning community which construct a common latent space shared by multiple input data sets.