Domain Adaptation with Few Labeled Source Samples by Graph Regularization
Sign Up to like & getrecommendations! Published in 2019 at "Neural Processing Letters"
DOI: 10.1007/s11063-019-10075-z
Abstract: Domain Adaptation aims at utilizing source data to establish an exact model for a related but different target domain. In recent years, many effective models have been proposed to propagate label information across domains. However,… read more here.
Keywords: graph regularization; source; domain adaptation; labeled source ... See more keywords
Semisupervised Hyperspectral Image Classification via Superpixel-Based Graph Regularization With Local and Nonlocal Features
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2022.3191692
Abstract: Although a graph-based semisupervised learning (SSL) approach can utilize limited numbers of labeled samples for hyperspectral image (HSI) classification, it is difficult to use the large amount of pixels in an HSI to construct a… read more here.
Keywords: superpixel based; classification; graph regularization; based graph ... See more keywords
Low Rank Matrix Factorization Algorithm Based on Multi-Graph Regularization for Detecting Drug-Disease Association.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE/ACM transactions on computational biology and bioinformatics"
DOI: 10.1109/tcbb.2023.3274587
Abstract: Detecting potential associations between drugs and diseases plays an indispensable role in drug development, which has also become a research hotspot in recent years. Compared with traditional methods, some computational approaches have the advantages of… read more here.
Keywords: rank matrix; low rank; regularization; graph regularization ... See more keywords
Sparse Graph Regularization for Hyperspectral Remote Sensing Image Classification
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2016.2641985
Abstract: Regularization has appeared explicitly in hyperspectral image (HSI) classification community, which serves as a promising paradigm for leveraging labeled and unlabeled information, computer’s automation and user’s interaction, spectral and spatial information, and so on. Graph-based… read more here.
Keywords: classification; graph regularization; sparse graph; regularization ... See more keywords