English
Related papers

Related papers: A conditional construction of restricted isometrie…

200 papers

Mixture transition distribution time series models build high-order dependence through a weighted combination of first-order transition densities for each one of a specified number of lags. We present a framework to construct stationary…

Methodology · Statistics 2025-02-25 Xiaotian Zheng , Athanasios Kottas , Bruno Sansó

The random matrix model is popular in extended object tracking, due to its relative simplicity and versatility. In this model, the extended object state consists of a kinematic vector for the position and motion parameters (velocity, etc),…

Signal Processing · Electrical Eng. & Systems 2019-07-24 Karl Granström , Jakob Bramstång

Penalized estimation principle is fundamental to high-dimensional problems. In the literature, it has been extensively and successfully applied to various models with only structural parameters. As a contrast, in this paper, we apply this…

Statistics Theory · Mathematics 2017-08-03 Jianqing Fan , Runlong Tang , Xiaofeng Shi

We develop here a simple quantisation formalism that make use of Lie algebra properties of the Poisson bracket. When the brackets $\{H,\phi_i\}$ and $\{\phi_i,\phi_j\}$, where $H$ is the Hamiltonian and $\phi_i$ are primary and secondary…

Quantum Physics · Physics 2007-05-23 Petre Diţă

We detail the construction of a weak Poisson bracket over a submanifold of a smooth manifold M with respect to a local foliation of this submanifold. Such a bracket satisfies a weak type Jacobi identity but may be viewed as a usual Poisson…

Mathematical Physics · Physics 2016-05-17 Simon L. Lyakhovich , Matthew T. Peddie , Alexey A. Sharapov

Many applications of machine learning on discrete domains, such as learning preference functions in recommender systems or auctions, can be reduced to estimating a set function that is sparse in the Fourier domain. In this work, we present…

Machine Learning · Computer Science 2021-05-11 Chris Wendler , Andisheh Amrollahi , Bastian Seifert , Andreas Krause , Markus Püschel

One of the key issues in the acquisition of sparse data by means of compressed sensing (CS) is the design of the measurement matrix. Gaussian matrices have been proven to be information-theoretically optimal in terms of minimizing the…

Information Theory · Computer Science 2018-11-26 Ahmed Elzanaty , Andrea Giorgetti , Marco Chiani

First-class constraints constitute a potential obstacle to the computation of a Poisson bracket in Dirac's theory of constrained Hamiltonian systems. Using the pseudoinverse instead of the inverse of the matrix defined by the Poisson…

Chaotic Dynamics · Physics 2014-12-17 C. Chandre

Mixed (asymmetric) orthogonal arrays (MOAs) generalize classical orthogonal arrays by allowing columns over different alphabets. However, their study requires very different structural tools than those used for symmetric orthogonal arrays…

Information Theory · Computer Science 2026-03-20 Maryam Bajalan , Peter Boyvalenkov , Ferruh Özbudak

In this paper we study the exponential decay of posterior probability of a set of sources and conditioning by rare sources for both uniform and general prior distributions of sources. The decay rate is determined by $L$-divergence and rare…

Statistics Theory · Mathematics 2007-06-13 M. Grendar

Simple transformation formulas between fermion matrices and observables, and numerical values of quark matrices, are obtained on a particular weak basis with one quark matrix diagonal and the other with vanishing elements 1-1, 1-3 and 3-1,…

High Energy Physics - Phenomenology · Physics 2011-02-01 D. Falcone , F. Tramontano

The desirable properties when constructing collections of subspaces often include the algebraic constraint that the projections onto the subspaces yield a resolution of the identity like the projections onto lines spanned by vectors of an…

Functional Analysis · Mathematics 2021-06-02 Emily J. King

\emph{Koopman Regularization} is a constrained optimization-based method to learn the governing equations from sparse and corrupted samples of the vector field. \emph{Koopman Regularization} extracts a functionally independent set of…

Dynamical Systems · Mathematics 2026-02-25 Ido Cohen

Consider the problem of recovering an unknown signal from undersampled measurements, given the knowledge that the signal has a sparse representation in a specified dictionary $D$. This problem is now understood to be well-posed and…

Information Theory · Computer Science 2015-06-09 Felix Krahmer , Deanna Needell , Rachel Ward

Reduced-Order Modelling of the Bending of an Array of An array of micromirrors for beam steering optical switching has been designed in a thick polysilicon technology. A novel semi-analytical method to calculate the static characteristics…

Other Computer Science · Computer Science 2007-11-29 A. Molfese , A. Nannini , F. Pieri

In this study, Bayesian inference is developed for structural vector autoregressive models in which the structural parameters are identified via Markov-switching heteroskedasticity. In such a model, restrictions that are just-identifying in…

Econometrics · Economics 2023-11-13 Helmut Lütkepohl , Tomasz Woźniak

The problem of imaging extended targets (sources or scatterers) is formulated in the framework of compressed sensing with emphasis on subwavelength resolution. The proposed formulation of the problems of inverse source/scattering is…

Optics · Physics 2009-09-15 Albert C. Fannjiang

Let L be a restricted Lie algebra over a field of positive characteristic. We survey the known results about the Lie structure of the restricted enveloping algebra u(L) of L. Related results about the structure of the group of units and the…

Rings and Algebras · Mathematics 2015-11-02 Salvatore Siciliano , Hamid Usefi

An oscillator algebra and the associated Fock space with reflecting boundary and generalized statistics are constructed and is generalized to the multicomponent case. The oscillator algebra depends manifestly on the reflection factor and…

High Energy Physics - Theory · Physics 2007-05-23 Liu Zhao

We consider the problem of learning low-rank tensors from partial observations with structural constraints, and propose a novel factorization of such tensors, which leads to a simpler optimization problem. The resulting problem is an…

Machine Learning · Computer Science 2023-05-16 Jayadev Naram , Tanmay Kumar Sinha , Pawan Kumar
‹ Prev 1 8 9 10 Next ›