Learning a representation with the block-diagonal structure for pattern classification
Sign Up to like & getrecommendations! Published in 2019 at "Pattern Analysis and Applications"
DOI: 10.1007/s10044-019-00858-4
Abstract: Sparse-representation-based classification (SRC) has been widely studied and developed for various practical signal classification applications. However, the performance of a SRC-based method is degraded when both the training and test data are corrupted. To counteract… read more here.
Keywords: classification; representation block; diagonal structure; block diagonal ... See more keywords
A note on block diagonal and block triangular preconditioners for complex symmetric linear systems
Sign Up to like & getrecommendations! Published in 2018 at "Numerical Algorithms"
DOI: 10.1007/s11075-018-0520-4
Abstract: In this note, the additive block diagonal preconditioner (Bai et al., Numer. Algorithms 62, 655–675 2013) and the block triangular preconditioner (Pearson and Wathen, Numer. Linear Algebra Appl. 19, 816–829 2012) are further studied and… read more here.
Keywords: note block; block; triangular preconditioners; block diagonal ... See more keywords
Multi-View Subspace Clustering With Block Diagonal Representation
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2923614
Abstract: Self-representation model has made good progress for a single view subspace clustering. This paper proposed the multi-view subspace clustering model based on self-representation. This model assumes that the samples from different classes are embedded in… read more here.
Keywords: representation; block diagonal; model; multi view ... See more keywords
Unsupervised Band Selection Using Block-Diagonal Sparsity for Hyperspectral Image Classification
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2017.2751082
Abstract: In order to alleviate the negative effect of curse of dimensionality, band selection is a crucial step for hyperspectral image (HSI) processing. In this letter, we propose a novel unsupervised band selection approach to reduce… read more here.
Keywords: unsupervised band; hyperspectral image; band; band selection ... See more keywords
An Efficient Approximate Expectation Propagation Detector With Block-Diagonal Neumann-Series
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Circuits and Systems I: Regular Papers"
DOI: 10.1109/tcsi.2022.3229690
Abstract: Expectation propagation (EP) achieves near-optimal performance for large-scale multiple-input multiple-output (L-MIMO) detection, however, at the expense of unaffordable matrix inversions. To tackle the issue, several low-complexity EP detectors have been proposed. However, they all fail… read more here.
Keywords: neumann series; diagonal neumann; block diagonal; expectation propagation ... See more keywords
Block Diagonal Representation Learning for Hyperspectral Band Selection
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2023.3266811
Abstract: Hyperspectral band selection is viewed as an effective dimension reduction method. Recently, researchers present graph-based clustering for hyperspectral image (HSI) processing. However, most of them conduct clustering on a fixed data matrix so that it… read more here.
Keywords: band; representation learning; hyperspectral band; band selection ... See more keywords
Subspace Clustering by Block Diagonal Representation
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2018.2794348
Abstract: This paper studies the subspace clustering problem. Given some data points approximately drawn from a union of subspaces, the goal is to group these data points into their underlying subspaces. Many subspace clustering methods have… read more here.
Keywords: diagonal representation; block; subspace clustering; block diagonal ... See more keywords