random matrix
Random Matrix Theory applied to the Estimation of Collision Multiplicities
... Recent advances in the Random Matrix Theory (RMT) field have brought into light several properties on the distribution of both signal and noise eigenvalues [20], [21]. These properties have been used in ...
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Quantum chaos and random matrix theoryfor fidelity decay in quantum computationswith static imperfections
... Klaus M. Frahm, Robert Fleckinger and Dima L. Shepelyansky Laboratoire de Physique Th´eorique, UMR 5152 du CNRS, Universit´e Paul Sabatier, 31062 Toulouse Cedex 4, France Received: December 13, 2003 Abstract. We ...
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Random matrix study of the phase structure of QCD with two colors
... A final comment concerns the evolution of the baryon density as a function of µ. We have not displayed baryon densities for µ ≫ µ c because random matrix models describe only the contribution of soft modes. ...
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Extension of Random Matrix Theory to the L-moments for Robust Portfolio Allocation
... noise. Random matrix theory developed by physicians in order to understand the energy process for which sources are unknown (see Edelman, 1989), gives a solution for filtering ...of Random ...
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Orbit measures, random matrix theory and interlaced determinantal processes
... of random matrix theory (RMT) is computation of eigen- value ...covariance matrix of a Gaussian vector. In 1951, Wigner [62] introduced random Hermitian matrices in physics, with the idea that ...
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Universal distribution of random matrix eigenvalues near the "birth of a cut'' transition.
... Introduction Random matrix models [20, 13] have been studied in relationship with many areas of physics and ...large random matrix depends only on the symmetries of the matrix ensemble, ...
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A Random Matrix Analysis of Learning with α-Dropout
... on random matrix theory, we have analyzed the effect of the α-Dropout layer on a one layer neural network, which allowed us to have a deeper understanding of the impact of this ...
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Random matrix model for antiferromagnetism and superconductivity on a two-dimensional lattice
... the random matrix approach and microscopic models may well be a consequence of the neglect of density of states effects in the potential of ...a random matrix model will not give a definite ...
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Temperature dependence in random matrix models with pairing condensates
... The deterministic part of the Dirac operator is given as ω + (µ f , T ) = ω − (µ f , T ) = (1 spin ⊗ 1 color ) (µ f + is f πT ) , (10) where the choice of s f = ±1 follows a selection rule. First, s f is taken positive ...
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The Dynamics of Learning: A Random Matrix Approach
... selected subset (called a mini-batch) of the training data is used to compute the gradient and descend one step along with the opposite direction of this gradient in each iteration. In this scenario, one of major concern ...
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A Random Matrix and Concentration Inequalities framework for Neural Networks Analysis
... networks, random matrix theory, concentration inequalities, extreme learning ...the random ini- tialization point of the backpropagation learning algorithm, essentially the same performances are ...
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A random matrix model for color superconductivity at zero chemical potential
... fects. Random matrix models include only direct ...unequal matrix indices k and l in ...the random background in order to reproduce the modified four-fermion ...the matrix model that ...
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High-Dimensional MVDR Beamforming: Optimized Solutions Based on Spiked Random Matrix Models
... Spiked Random Matrix Models Liusha Yang ∗ , Matthew ...variance matrix of the received signals, which must be estimated from ...in random matrix theory, we propose robust beamforming ...
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Random Matrix Theory applied to the Estimation of Collision Multiplicities
... Recent advances in the Random Matrix Theory (RMT) field have brought into light several properties on the distribution of both signal and noise eigenvalues [20], [21]. These properties have been used in ...
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Applications of large random matrix to high dimensional statistical signalprocessing
... normalized matrix Σ (L) N = B (L) N +W (L) N can be interpreted as a finite rank deterministic perturbation of the structured random matrix W (L) N ...Hankel random matrix W (L) N was ...
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Random matrix models for phase diagrams
... the random and the deterministic parts of the Hamiltonians. Here, the random part of the Hamiltonian was not intended to describe randomly fluctuating processes or statistical ...and random ...
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Random Matrix Theory Proves that Deep Learning Representations of GAN-data Behave as Gaussian Mixtures
... Gram matrix is seen to follow the same spectral behavior for GAN-data as for the GMM model which is a natural consequence of the universality result of Theorem ...Gram matrix spectrum of the representations ...
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Beyond universality in random matrix theory
... From an application viewpoint, it is very valuable to have an estimate for the departure from universality. Real problems require that n be finite, not infinite, and it has long been observed computationally that ∞ ...
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Random matrix model for chiral symmetry breaking and color superconductivity in QCD at finite density
... interactions which in a four-dimensional field theory would respect color SU (N c ) and Lorentz invariance in the vacuum. Therefore, we choose a single variance Σ Ca for all channels which transform equally under color ...
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A random matrix analysis of random Fourier features: beyond the Gaussian kernel, a precise phase transition, and the corresponding double descent
... Random matrix theory. From a random matrix theory perspective, nonlinear Gram matrices of the type Σ T X Σ X have recently received an unprecedented research interests, due to their close ...
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