Results 11 to 20 of about 9,586,369 (306)
Review of Dimension Reduction Methods
Journal of Data Analysis and Information Processing, 2021 Purpose: This study sought to review the characteristics, strengths, weaknesses variants, applications areas and data types applied on the various Dimension Reduction techniques.
S. Nanga +7 more
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Dimension reduction of noisy interacting systems
Physical Review Research, 2023 We consider a class of models describing an ensemble of identical interacting agents subject to multiplicative noise. In the thermodynamic limit, these systems exhibit continuous and discontinuous phase transitions in a, generally, nonequilibrium setting.
Niccolò Zagli +3 more
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Strong and weak principles of neural dimension reduction [PDF]
Neurons, Behavior, Data analysis, and Theory, 2020 If spikes are the medium, what is the message? Answering that question is driving the development of large-scale, single neuron resolution recordings from behaving animals, on the scale of thousands of neurons.
M. Humphries
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Dimension Reduction Regression in R
Journal of Statistical Software, 2002 Regression is the study of the dependence of a response variable y on a collection predictors p collected in x. In dimension reduction regression, we seek to find a few linear combinations β1x,...,βdx, such that all the information about the regression ...
Sanford Weisberg
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Cumulative Median Estimation for Sufficient Dimension Reduction
Stats, 2021 In this paper, we present the Cumulative Median Estimation (CUMed) algorithm for robust sufficient dimension reduction. Compared with non-robust competitors, this algorithm performs better when there are outliers present in the data and comparably when ...
Stephen Babos, Andreas Artemiou
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Multi-Label Learning via Feature and Label Space Dimension Reduction
IEEE Access, 2020 In multi-label learning, each object belongs to multiple class labels simultaneously. In the data explosion age, the size of data is often huge, i.e., large number of instances, features and class labels.
Jun Huang +4 more
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A data partition strategy for dimension reduction
AIMS Mathematics, 2020 Based on the idea that different data contributes differently to dimension reduction, we propose a weighted affinity propagation strategy to partition the data into representative data and common data. The representative data have dominant features while
Li Liu +5 more
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Hyperspectral Image Classification via Information Theoretic Dimension Reduction
Remote Sensing, 2023 Hyperspectral images (HSIs) are one of the most successfully used tools for precisely and potentially detecting key ground surfaces, vegetation, and minerals.
Md Rashedul Islam +4 more
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Dimension Reduction via Colour Refinement [PDF]
, 2014 Colour refinement is a basic algorithmic routine for graph isomorphism testing, appearing as a subroutine in almost all practical isomorphism solvers. It partitions the vertices of a graph into "colour classes" in such a way that all vertices in the same
A. Cardon +7 more
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High Dimensional Bayesian Optimization via Supervised Dimension Reduction [PDF]
International Joint Conference on Artificial Intelligence, 2019 Bayesian optimization (BO) has been broadly applied to computational expensive problems, but it is still challenging to extend BO to high dimensions. Existing works are usually under strict assumption of an additive or a linear embedding structure for ...
Miao Zhang, Huiqi Li, S. Su
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