Yuwu Lu
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Invertible Projection and Conditional Alignment for Multi-Source Blended-Target Domain Adaptation Open
Multi-source domain adaptation (MSDA), which utilizes multiple source domains to align the distribution of a single target domain, is a popular and challenging setting in domain adaptation (DA). However, existing MSDA approaches are diffic…
Collaborative Semantic Consistency Alignment for Blended-Target Domain Adaptation Open
Blended-target domain adaptation (BTDA) leverages learned source knowledge to adapt the model to a blended-target domain that is composed of multiple unlabeled sub-target domains with distinct statistical characteristics. The existing BTDA…
Towards Discriminability with Distribution Discrepancy Constrains for Multisource Domain Adaptation Open
Multisource domain adaptation (MDA) is committed to mining and extracting data concerning target tasks from several source domains. Many recent studies have focused on extracting domain-invariant features to eliminate domain distribution d…
Discriminative Invariant Alignment for Unsupervised Domain Adaptation Open
As one of the most prevalent branches of transfer learning, domain adaptation is dedicated to generalizing the knowledge of a source domain to a target domain to perform machine learning tasks. In domain adaptation, the key strategy is to …
Structurally Incoherent Low-Rank Nonnegative Matrix Factorization for Image Classification Open
As a popular dimensionality reduction method, nonnegative matrix factorization (NMF) has been widely used in image classification. However, the NMF does not consider discriminant information from the data themselves. In addition, most NMF-…
Low-Rank 2-D Neighborhood Preserving Projection for Enhanced Robust Image Representation Open
2-D neighborhood preserving projection (2DNPP) uses 2-D images as feature input instead of 1-D vectors used by neighborhood preserving projection (NPP). 2DNPP requires less computation time than NPP. However, both NPP and 2DNPP use the L 2…
Nuclear Norm-Based 2DLPP for Image Classification Open
Two-dimensional locality preserving projections (2DLPP) that use 2D image representation in preserving projection learning can preserve the intrinsic manifold structure and local information of data. However, 2DLPP is based on the Euclidea…
Nonnegative Discriminant Matrix Factorization Open
\n\tNonnegative matrix factorization (NMF), which aims at obtaining the nonnegative low-dimensional representation of data, has received wide attention. To obtain more effective nonnegative discriminant bases from the original NMF, in this…