نتایج جستجو برای: laplace and regression analyses

تعداد نتایج: 16862446  

2009
Mykhaylo Shkolnikov

This paper continues the study of metastable behaviour in disordered mean field models initiated in [2], [3]. We consider the generalized Hopfield model with finitely many independent patterns ξ1, . . . , ξP where the patterns have i.i.d. components and the components of patterns ξ1, . . . ξp have absolutely continuous distributions on [−1, 1] whereas the components of patterns ξp+1, . . . , ξP...

Journal: :Neural computation 2016
Kishan Wimalawarne Ryota Tomioka Masashi Sugiyama

We theoretically and experimentally investigate tensor-based regression and classification. Our focus is regularization with various tensor norms, including the overlapped trace norm, the latent trace norm, and the scaled latent trace norm. We first give dual optimization methods using the alternating direction method of multipliers, which is computationally efficient when the number of trainin...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه محقق اردبیلی - دانشکده علوم کشاورزی 1391

abstract: the potato tuberworm, phthorimaea operculella (zeller), is an important insect pest of potato (solanum tuberosum l.) in the storage and field in most parts of the world especially in tropical and subtropical regions due to its close relationship with the host, high reproductive potential and high economic losses. information on host preference, life table parameters and digestive en...

G.D Kedar J.J Tripathi, K.C Deshmukh

The present work is aimed at analyzing the thermoelastic disturbances in a circular plate of finite thickness and infinite extent subjected to constant initial temperature and axisymmetric heat supply. Integral transform technique is used. Analytic solutions for temperature, displacement and stresses are derived within the context of unified system of equations in generalized thermoelasticity i...

2008
Efang Kong Yingcun Xia

Regression quantiles, along with the dual methods of regression rank scores, can be considered one of the major statistical breakthroughs of the past decades. Its advantages over the other estimation methods have been well investigated. Regression quantile methods provide a much more complete statistical analysis of the stochastic relationships among variables; in addition, they are more robust...

2009
Mirko Tarulli

We prove an analogue of a classical asymptotic stability result of standing waves of the Schrödinger equation originating in work by Soffer and Weinstein. Specifically, our result is a transposition on the lattice Z of a result by Mizumachi [M1] and it involves a discrete Schrödinger operator H = −∆+q. The decay rates on the potential are less stringent than in [M1], since we require q ∈ l1,1. ...

2009
Mirko Tarulli

We prove an analogue of a classical asymptotic stability result of standing waves of the Schrödinger equation originating in work by Soffer and Weinstein. Specifically, our result is a transposition on the lattice Z of a result by Mizumachi [M1] and it involves a discrete Schrödinger operator H = −∆+q. The decay rates on the potential are less stringent than in [M1], since we require q ∈ l1,1. ...

2013
Fumio Hiroshima József Lőrinczi

The behaviour of the spectral edges (embedded eigenvalues and resonances) is discussed at the two ends of the continuous spectrum of non-local discrete Schrödinger operators with a δ-potential. These operators arise by replacing the discrete Laplacian by a strictly increasing C1-function of the discrete Laplacian. The dependence of the results on this function and the lattice dimension are expl...

2008
Uzy Smilansky

The Exterior-Interior duality expresses a deep connection between the Laplace spectrum in bounded and connected domains in R, and the scattering matrices in the exterior of the domains. Here, this link is extended to the study of the spectrum of the discrete Laplacian on finite graphs. For this purpose, two methods are devised for associating scattering matrices to the graphs. The Exterior -Int...

Journal: :International Journal of Forecasting 2021

We develop a Bayesian median autoregressive (BayesMAR) model for time series forecasting. The proposed method utilizes time-varying quantile regression at the median, favorably inheriting robustness of in contrast to widely used mean-based methods. Motivated by working Laplace likelihood approach regression, BayesMAR adopts parametric bearing same structure as models altering Gaussian error Lap...

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