English
Related papers

Related papers: Towards Spectral Convergence of Locally Linear Emb…

200 papers

Based on the Riemannian manifold model, we study the asymptotic behavior of a widely applied unsupervised learning algorithm, locally linear embedding (LLE), when the point cloud is sampled from a compact, smooth manifold with boundary. We…

Statistics Theory · Mathematics 2024-06-27 Hau-tieng Wu , Nan Wu

In this paper, we investigate the eigenvalue problem for a non-local dispersal operator defined on a bounded spatial domain with Neumann-type boundary conditions. Unlike the classical Laplacian, the non-local operator lacks compactness,…

Spectral Theory · Mathematics 2026-05-26 Maciej Tadej

Using the method of similar operators we study an even order differential operator with periodic, semiperiodic, and Dirichlet boundary conditions. We obtain asymptotic formulas for eigenvalues of this operator and estimates for its spectral…

Spectral Theory · Mathematics 2018-02-20 Dmitry M. Polyakov

In this chapter we are examining several iterative methods for solving nonlinear eigenvalue problems. These arise in variational image-processing, graph partition and classification, nonlinear physics and more. The canonical eigenproblem we…

Numerical Analysis · Mathematics 2020-10-07 Guy Gilboa

We consider a singular perturbed eigenvalue problem for Laplace operator in a cylinder with frequent interchange of type of boundary condition on a lateral surface. These boundary conditions are prescribed by partition of lateral surface in…

Mathematical Physics · Physics 2007-05-23 Denis I. Borisov

We study a Dirichlet spectral problem for a second-order elliptic operator with locally periodic coefficients in a thin domain. The boundary of the domain is assumed to be locally periodic. When the thickness of the domain $\varepsilon$…

Analysis of PDEs · Mathematics 2021-03-08 Klas Pettersson

Explicit representations of the eigenvalues of the peridynamic operator have been recently derived in [5]. These representations are given in terms of generalized hypergeometric functions. Asymptotic analysis of the hypergeometric functions…

Mathematical Physics · Physics 2023-08-21 Bacim Alali , Nathan Albin , Thinh Dang

The purpose of this work is to study spectral methods to approximate the eigenvalues of nonlocal integral operators. Indeed, even if the spatial domain is an interval, it is very challenging to obtain closed analytical expressions for the…

Numerical Analysis · Mathematics 2021-10-13 Luciano Lopez , Sabrina Francesca Pellegrino

In this paper following the same methods in [M. Kadakal, O. Sh. Mukhtarov, Sturm-Liouville problems with discontinuities at two points, Comput. Math. Appl., 54 (2007) 1367-1379] we investigate discontinuous two-point boundary value problems…

Classical Analysis and ODEs · Mathematics 2013-04-23 Erdoğan Şen , Oktay Mukhtarov

We introduce a framework for subspace methods which approximate the spectra of self-adjoint, unbounded operators in a local region. Using the projection-valued measure, we derive integrated spectral inequalities that also apply to unbounded…

Numerical Analysis · Mathematics 2026-01-06 Timothy Stroschein

We consider a general second-order elliptic differential operator on a domain with a cylindrical end. We impose Dirichlet boundary conditions on the boundary with the exception of a small set, where we impose Neumann boundary conditions.…

Spectral Theory · Mathematics 2017-10-06 André Froehly

Nonlinear manifold learning algorithms, such as diffusion maps, have been fruitfully applied in recent years to the analysis of large and complex data sets. However, such algorithms still encounter challenges when faced with real data. One…

Mathematical Physics · Physics 2015-05-25 Carmeline J. Dsilva , Ronen Talmon , Ronald R. Coifman , Ioannis G. Kevrekidis

We study an indefinite spectral problem for a second-order self-adjoint elliptic operator in an asymptotically thin cylinder. The operator coefficients and the spectral density function are assumed to be locally periodic in the axial…

Analysis of PDEs · Mathematics 2025-07-01 Srinivasan Aiyappan , Aditi Chattaraj , Irina Pettersson

We analyze the performance of a class of manifold-learning algorithms that find their output by minimizing a quadratic form under some normalization constraints. This class consists of Locally Linear Embedding (LLE), Laplacian Eigenmap,…

Machine Learning · Statistics 2008-06-17 Y. Goldberg , A. Zakai , D. Kushnir , Y. Ritov

The spectral properties of the Frobenius-Perron operator of one-dimensional maps are studied when approaching a weakly intermittent situation. Numerical investigation of a particular family of maps shows that the spectrum becomes extremely…

chao-dyn · Physics 2009-10-28 Z. Kaufmann , H. Lustfeld , J. Bene

We study a class of nonlinear eigenvalue problems which involves a convolution operator as well as a superlinear nonlinearity. Our variational existence proof is based on constrained optimization and provides a one-parameter family of…

Mathematical Physics · Physics 2020-03-16 Michael Herrmann , Karsten Matthies

The aim of this article is to analyze the asymptotic behaviour of the eigenvalues of elliptic operators in divergence form with mixed boundary type conditions for domains that become unbounded in several directions, while they stay bounded…

Analysis of PDEs · Mathematics 2025-11-03 Prosenjit Roy , Itai Shafrir

We give a characterisation of the spectral properties of linear differential operators with constant coefficients, acting on functions defined on a bounded interval, and determined by general linear boundary conditions. The boundary…

Spectral Theory · Mathematics 2013-03-22 David Andrew Smith , Beatrice Pelloni

We present a finite element algorithm that computes eigenvalues and eigenfunctions of the Laplace operator for two-dimensional problems with homogeneous Neumann or Dirichlet boundary conditions or combinations of either for different parts…

Chaotic Dynamics · Physics 2007-05-23 G. Baez , F. Leyvraz , R. A. Mendez-Sanchez , T. H. Seligman

In the study of high-dimensional data, it is often assumed that the data set possesses an underlying lower-dimensional structure. A practical model for this structure is an embedded compact manifold with boundary. Since the underlying…

Machine Learning · Statistics 2025-08-22 Pei-Cheng Kuo , Nan Wu
‹ Prev 1 2 3 10 Next ›