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Co-Adjustment Learning for Co-Clustering

Cognitive Computation, 2021
Co-clustering simultaneously performs clustering on the sample and feature dimensions of the data matrix, so it can obtain better insight into the data than traditional clustering. Adjustment learning extracts valuable information from chunklets for unsupervised cluster learning in specific scenarios, but in fact it can be easily extended to semi ...
Ji Zhang 0012   +6 more
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Image Co-segmentation by Co-diffusion

Circuits, Systems, and Signal Processing, 2017
In this paper, a co-segmentation algorithm based on 3D heat diffusion named co-diffusion is proposed. The image set is considered as a metal cuboid, and the K heat sources with constant temperature, which maximize the sum of the temperature of the system under anisotropic heat diffusion, are found to cluster the image set.
Liman Liu, Kunqian Li, Xiangli Liao
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Feature co-shrinking for co-clustering

Pattern Recognition, 2018
Abstract Many real-world applications require multi-way feature selection rather than single-way feature selection. Multi-way feature selection is more challenging compared to single-way feature selection due to the presence of inter-correlation among the multi-way features.
Qi Tan 0001, Pei Yang 0001, Jingrui He
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Structural and Electronic Properties of Co-corrole, Co-corrin, and Co-porphyrin

Inorganic Chemistry, 2000
A quantitative study of the structure and electronic properties of Co-corrole, Co-corrin. and Co-porphyrin, using density functional theory, is reported. The structure of each macrocycle is optimized, with no symmetry constraints, by considering different spin states.
Rovira, C   +3 more
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CO DEHYDROGENASE

Annual Review of Microbiology, 1995
Structurally and functionally diverse CO dehydrogenases are key components of various energy-yielding pathways in aerobic and anaerobic microbes from the Bacteria and Archaea domains. Aerobic microbes utilize Mo-Fe-flavin CO dehydrogenases to oxidize CO in respiratory pathways.
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