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Found 4 papers, 1 papers with code
Learning Kernel for Conditional Moment-Matching Discrepancy-based Image Classification
KLN can simultaneously learn a more expressive kernel and label prediction distribution, thus, it can be used to improve the classification performance in both supervised and semi-supervised learning scenarios.
Unsupervised Domain Adaptation via Discriminative Manifold Propagation
Second, batch-wise training of deep learning limits the characterization of the global structure.
Discriminative Residual Analysis for Image Set Classification with Posture and Age Variations
Consequently, the crucial point of image set recognition is to mine the intrinsic connection or structural information from the image batches with variations.
Domain Adaptation and Image Classification via Deep Conditional Adaptation Network
In this paper, we consider a more general application scenario where the label distributions of the source and target domains are not the same.
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