Results 31 to 40 of about 3,322,529 (303)

New approaches on dimensionality reduction in hyperspectral images for classification purposes [PDF]

open access: yes, 2012
This paper presents a quasi-unsupervised methodology to detect endmembers within an hyperspectral scene and to derive a pixel-wise classification on its basis.
Rupert Mueller   +7 more
core   +1 more source

Adaptive Metric Dimensionality Reduction [PDF]

open access: yesTheoretical 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
openaire   +4 more sources

Dimensionality reduction by LPP‐L21

open access: yesIET 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
doaj   +1 more source

Factorization and regularization by dimensional reduction [PDF]

open access: yesPhysics 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.
openaire   +3 more sources

Dynamics of dimensional reduction

open access: yesPhysics 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
openaire   +1 more source

Local Feature Discriminant Projection [PDF]

open access: yes, 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
core   +1 more source

Neighbors-Based Graph Construction for Dimensionality Reduction

open access: yesIEEE 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
doaj   +1 more source

Rhythmic dynamics and synchronization via dimensionality reduction : application to human gait [PDF]

open access: yes, 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
core   +1 more source

AN ALTERNATIVE DIMENSIONAL REDUCTION PRESCRIPTION [PDF]

open access: yesModern 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
openaire   +3 more sources

Problem dimensionality reduction in design of optimal IIR filters [PDF]

open access: yes, 2002
A typical design of a digital IIR filter that is optimal in the sense of the weighted least squares criterion is performed by using a numerical optimisation procedure capable of searching for local minima of highly non-linear functions of vector ...
Tarczynski, A., A. Tarczynski
core   +1 more source

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