Results 31 to 40 of about 141,001 (306)
Adaptive Metric Dimensionality Reduction [PDF]
Theoretical Computer Science, 2013 We study adaptive data-dependent dimensionality reduction in the context of supervised learning in general metric spaces. Our main statistical contribution is a generalization bound for Lipschitz functions in metric spaces that are doubling, or nearly doubling.
Lee-Ad Gottlieb +2 more
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Dimensionality reduction by LPP‐L21
IET Computer Vision, 2018 Locality preserving projection (LPP) is one of the most representative linear manifold learning methods and well exploits intrinsic structure of data. However, the performance of LPP remarkably degenerate in the presence of outliers.
Shujian Wang +3 more
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mSystems, 2021 Microbiome data are sparse and high dimensional, so effective visualization of these data requires dimensionality reduction. To date, the most commonly used method for dimensionality reduction in the microbiome is calculation of between-sample microbial ...
George Armstrong +6 more
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Factorization and regularization by dimensional reduction [PDF]
Physics Letters B, 2005 Since an old observation by Beenakker et al, the evaluation of QCD processes in dimensional reduction has repeatedly led to terms that seem to violate the QCD factorization theorem. We reconsider the example of the process gg->ttbar and show that the factorization problem can be completely resolved.
Signer, A., Stöckinger, D.
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Local Feature Discriminant Projection [PDF]
, 2016 In this paper, we propose a novel subspace learning algorithm called Local Feature Discriminant Projection (LFDP) for supervised dimensionality reduction of local features.
Zhen, Xiantong +3 more
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Reduction dimensionality of hyperspectral imagery using genetic algorithm and mutual information and normalized mutual information as a fitness function [PDF]
, 2021 Hyperspectral images (HSI) present a wealth of information. It is distinguished by its high dimensionality. It served humanity in many fields. The quantity of HSI information represents a double-edged sword. As a consequence, their dimensionality must be
Merzouqi Maria +5 more
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Neighbors-Based Graph Construction for Dimensionality Reduction
IEEE Access, 2019 Dimensionality reduction is a fundamental task in the field of data mining and machine learning. In many scenes, examples in high-dimensional space usually lie on low-dimensional manifolds; thus, learning the low-dimensional embedding is important.
Hui Tian +3 more
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Rhythmic dynamics and synchronization via dimensionality reduction : application to human gait [PDF]
, 2010 Reliable characterization of locomotor dynamics of human walking is vital to understanding the neuromuscular control of human locomotion and disease diagnosis.
Small, M +15 more
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Dynamics of dimensional reduction
Physics Letters B, 1980 In d-dimensional unified theories that, along with gravity, contain an antisymmetric tensor field of rank s-1, preferential compactification of d-s or of s space-like dimensions is found to occur. This is the case in 11-dimensional supergravity where s = 4.
Peter G.O. FREUND, Mark A. RUBIN
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AN ALTERNATIVE DIMENSIONAL REDUCTION PRESCRIPTION [PDF]
Modern Physics Letters A, 1996 We propose an alternative dimensional reduction prescription which in respect with Green functions corresponds to dropping the extra spatial coordinate. From this, we construct the dimensionally reduced Lagrangians both for scalars and fermions, discussing bosonization and supersymmetry in the particular two-dimensional case.
Edelstein Glaubach, José Daniel +3 more
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