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Related papers: The Classical Multidimensional Scaling Revisited

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Inhomogeneous multidimensional cosmological models with a higher dimensional space-time manifold M=M_0 x M_1 x ... M_n are investigated under dimensional reduction to tensor-multi-scalar theories. In the Einstein conformal frame, these…

General Relativity and Quantum Cosmology · Physics 2009-10-28 M. Rainer , A. Zhuk

We study tridimensional tensors on the complex field from the point of view of hypermatrices, taking into consideration the problem of determining whether they are degenerate or not, concise or not, what is their essential format if they…

Algebraic Geometry · Mathematics 2026-05-12 Alessandro Gimigliano , Monica Idà

We study the model of a composite-scalar made of a pair of scalar fields in 6-2 epsilon dimensions, using equivalence to the renormalizable three-elementary-scalar model under the "compositeness condition." In this model, the…

High Energy Physics - Theory · Physics 2007-05-23 Keiichi Akama , Takashi Hattori

We study a method of reducing space dimension in multi-dimensional Black-Scholes partial differential equations as well as in multi-dimensional parabolic equations. We prove that a multiplicative transformation of space variables in the…

Computational Finance · Quantitative Finance 2014-06-10 Hyong-chol O , Yong-hwa Ro , Ning Wan

When the cosmological "constant" is derived from modern five-dimensional relativity, exact solutions imply that for small systems it scales in proportion to the square of the mass. However, a duality transformation implies that for large…

General Physics · Physics 2014-02-05 Paul S. Wesson , James M. Overduin

Principal component analysis continues to be a powerful tool in dimension reduction of high dimensional data. We assume a variance-diverging model and use the high-dimension, low-sample-size asymptotics to show that even though the…

Statistics Theory · Mathematics 2020-09-28 Sungkyu Jung

Many machine learning problems involve regressing variables on a non-Euclidean manifold -- e.g. a discrete probability distribution, or the 6D pose of an object. One way to tackle these problems through gradient-based learning is to use a…

Computer Vision and Pattern Recognition · Computer Science 2021-10-14 Romain Brégier

It is shown that the local coupling of a higher dimensional graviton to a closed degenerate two-form produces dimensional reduction by spontaneous breakdown of extra-dimensional translational symmetry. Four dimensional Poincar\'e invariance…

High Energy Physics - Theory · Physics 2007-05-23 P. Maraner

We examine three-dimensional metric deformations based on a tetrad transformation through the action the matrices of scalar fields. We describe by this approach to deformation the results obtained by Coll et al. in [1], where it is stated…

General Relativity and Quantum Cosmology · Physics 2015-02-05 Daniela Pugliese , Cosimo Stornaiolo

We use the single-cluster Monte Carlo update algorithm to simulate the three-dimensional classical Heisenberg model in the critical region on simple cubic lattices of size $L^3$ with $L=12, 16, 20, 24, 32, 40$, and $48$. By means of…

High Energy Physics - Lattice · Physics 2009-10-22 Christian Holm , Wolfhard Janke

Stochastic nonequilibrium exclusion models are treated using a real space scaling approach. The method exploits the mapping between nonequilibrium and quantum systems, and it is developed to accommodate conservation laws and duality…

Statistical Mechanics · Physics 2009-11-11 T. Hanney , R. B. Stinchcombe

We investigate cosmologies with an arbitrary number of scalars and the most general multi-exponential potential. By formulating the equations of motion in terms of autonomous systems we complete the classification of power-law and de Sitter…

High Energy Physics - Theory · Physics 2014-11-18 Andres Collinucci , Mikkel Nielsen , Thomas Van Riet

We use machine learning methods to approximate a classical density functional. As a study case, we choose the model problem of a Lennard Jones fluid in one dimension where there is no exact solution available and training data sets must be…

Soft Condensed Matter · Physics 2019-03-04 Shang-Chun Lin , Martin Oettel

The Gini Multidimensional Scaling (Gini MDS) framework extends the Euclidean multidimensional scaling. We introduce a Gini pseudo-distance based on values and their ranks that depends on a fine-tunable hyperparameter. This pseudo-distance…

Machine Learning · Computer Science 2026-05-26 Cassandra Mussard , Stéphane Mussard

In this paper, we propose a unified algorithmic framework for solving many known variants of \mds. Our algorithm is a simple iterative scheme with guaranteed convergence, and is \emph{modular}; by changing the internals of a single…

Machine Learning · Computer Science 2010-03-31 Arvind Agarwal , Jeff M. Phillips , Suresh Venkatasubramanian

We consider superintegrability in classical mechanics in the presence of magnetic fields. We focus on three-dimensional systems which are separable in Cartesian coordinates. We construct all possible minimally and maximally superintegrable…

Mathematical Physics · Physics 2020-03-13 Antonella Marchesiello , Libor Šnobl

The article contains some important classes of multisets. Combinatorial proofs of problems on the number of m-submultisets and m-permutations of multiset elements are considered and effective algorithms for their calculation are given. In…

General Mathematics · Mathematics 2020-09-04 Oleksandr Makhnei , Roman Zatorskii

Classical dimensional analysis is one of the cornerstones of qualitative physics and is also used in the analysis of engineering systems, for example in engineering design. The basic power product relationship in dimensional analysis is…

Data Analysis, Statistics and Probability · Physics 2013-04-25 M. A. Atherton , R. A. Bates , H. P. Wynn

Multidimensionality of our Universe is one of the most intriguing assumption in modern physics. It follows naturally from theories unifying different fundamental interactions with gravity, e.g. M/string theory. The idea has received a great…

General Relativity and Quantum Cosmology · Physics 2011-12-01 Tamerlan Saidov

We propose and analyze the moving median absolute deviation (MMAD) as a robust depth construction based on the median absolute distance functional with particular emphasis on its local geometry and probabilistic structure. In the univariate…

Methodology · Statistics 2026-05-07 Elsayed Elamir
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