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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,051 papers · 148 categories

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25.0%50.0%75.0%100.0% · May 199319922001200920182026
48 results for kernel expansions

Researchers derived heat kernel expansions for non-compact spaces using Witten deformation.

problem Heat kernel expansions on non-compact spaces, especially for Witten Laplacians.
method Introduced parabolic distance and used it to derive asymptotic expansions.
result Derived an asymptotic expansion of trace of heat kernel for small-time tt.

Study Szegő kernel on non-compact CR manifolds with specific conditions.

problem Analyzing Szegő kernel on non-compact CR manifolds.
method Establish Szegő kernel asymptotic expansions on non-compact strictly pseudoconvex CR manifolds with transversal CR R\mathbb{R}-action under natural geometric conditions.
result Szegő kernel asymptotic expansions established on non-compact CR manifolds.

The paper examines how kernel approximations affect Gaussian process regression in large data applications.

problem Effect of kernel approximations on Gaussian process regression in large data applications.
method Unified framework to analyze Gaussian process regression under computational and epistemic misspecification.
result Theoretical analysis of Gaussian process regression under various misspecifications.

Let XX be a compact connected strongly pseudoconvex CR manifold of dimension 2n+1,n12n+1, n \ge 1 with a transversal CR S1S^1 action on XX. We establish an asymptotic expansion for the mm-th Fourier component of the Szegő kernel function as mm\rightarrow\infty, where the expansion involves a contribution in terms of a d…

2016-10-14abs ↗pdf ↗

Paper develops a new kernel expansion method using entropic optimal features for sparse and efficient kernel approximation.

problem Efficient kernel approximation with reduced computational cost and feature dissimilarity.
method Develops a novel optimal design maximizing entropy among kernel features, resulting in a sparse kernel expansion.
result Achieves optimal statistical accuracy with only $O(N^{ rac{1}{4}})$ features, significantly reducing time and space costs.

Many contemporary statistical learning methods assume a Euclidean feature space. This paper presents a method for defining similarity based on hyperspherical geometry and shows that it often improves the performance of support vector machine compared to other competing similarity measures. Specifically, the idea of usi…

2017-02-05abs ↗pdf ↗

Efficiently handles large support vectors in kernelized online learning.

problem Efficiency in communication for large support vectors in kernelized models.
method Extends a previously proposed protocol to kernelized online learners, introducing a novel communication criterion.
result Communication is bounded by the loss suffered, improving efficiency.

The analysis of holomorphic sections of high powers LNL^N of holomorphic ample line bundles LML\to M over compact Kähler manifolds has been widely applied in complex geometry and mathematical physics. The Tian-Yau-Zelditch's asymptotic expansion of the Szegö kernel of a circle bundle plays an important role in Kähler-E…

2004-05-05abs ↗pdf ↗

The paper analyzes how re-weighting helps in reducing variance in high-dimensional kernel methods under covariate shifts.

problem The challenge of high-dimensional kernel methods under covariate shifts and the role of re-weighting.
method Derives asymptotic expansion of high-dimensional kernels under covariate shifts, analyzes bias-variance decomposition, and characterizes the regularized kernel.
result Re-weighting helps in decreasing variance and can be seen as a data-dependent regularization.

We study the relationship between the geometry and the Laplace spectrum of a Riemannian orbifold O via its heat kernel; as in the manifold case, the time-zero asymptotic expansion of the heat kernel furnishes geometric information about O. In the case of a good Riemannian orbifold (i.e., an orbifold arising as the orbi…

2008-05-20abs ↗pdf ↗

The paper develops a multi-kernel method with sparsity constraint for regression.

problem Developing a robust regression method with sparsity constraints.
method Banach-space formulation, generalized total-variation regularization, multi-kernel expansion, adaptive kernel positions, 1\ell_1 penalty on coefficients.
result The method achieves sparsity in the kernel coefficients, reducing the number of active kernels to the number of data points.

Kernel methods have great promise for learning rich statistical representations of large modern datasets. However, compared to neural networks, kernel methods have been perceived as lacking in scalability and flexibility. We introduce a family of fast, flexible, lightly parametrized and general purpose kernel learning …

2014-12-19abs ↗pdf ↗

We prove a graph theoretic closed formula for coefficients in the Tian-Yau-Zelditch asymptotic expansion of the Bergman kernel. The formula is expressed in terms of the characteristic polynomial of the directed graphs representing Weyl invariants. The proof relies on a combinatorial interpretation of a recursive formul…

2011-03-15abs ↗pdf ↗

The paper studies finite TYCZ expansions on Kaehler manifolds and their relation to cscK metrics.

problem Finite TYCZ expansions on Kaehler manifolds and their connection to cscK metrics.
method Analyzes finite TYCZ expansions on Kaehler manifolds and their properties.
result Finite TYCZ expansions imply polynomial behavior of certain metrics and vanishing of log-term in Szegö kernel.

Researchers calculate entropy of heat kernel on manifolds for very small times.

problem Estimating entropy of heat kernel on compact Riemannian manifolds for small times.
method Asymptotic expansion, polynomial expressions in curvature tensor components.
result First three coefficients of entropy expansion computed and expressed as polynomials.

The study examines Bergman kernels on complex manifolds with boundary and their asymptotic expansions.

problem Analyzing Bergman kernels on complex manifolds with boundary and their asymptotic behavior.
method Establishing asymptotic expansions of partial Bergman kernels for high-frequency Fourier modes on R\mathbb{R}-symmetric complex manifolds with boundary.
result Established R\mathbb{R}-equivariant extension results for biholomorphic maps between weakly pseudoconvex domains.

Let φC(Cn)φ\in C^\infty(\Complex^n) be a given real valued function. We assume that $\pr\ddbarφ$ is non-degenerate of constant signature (n,n+)(n_-,n_+) on Cn\Complex^n. When q=nq=n_-, it is well-known that the Bergman kernel for (0,q)(0,q) forms with respect to the kk-th weight e2kφe^{-2kφ}, k>0k>0, admits a full asymptotic expansi…

2012-08-19abs ↗pdf ↗

We consider second-order elliptic partial differential operators acting on sections of vector bundles over a compact Riemannian manifold without boundary, working without the assumption of Laplace-like principal part NμNμ-\N^μ\N_μ. Our objective is to obtain information on the asymptotic expansions of the corresponding r…

1999-05-03abs ↗pdf ↗

Let Hh=h2L+VH_h = h^2 L +V where LL is a self-adjoint Laplace type operator acting on sections of a vector bundle over a compact Riemannian manifold and VV is a symmetric endomorphism field. We derive an asymptotic expansion for the heat kernel of HhH_h as h0h \to 0. As a consequence we get an asymptotic expansion for the …

2008-05-06abs ↗pdf ↗

Study asymptotics of Poisson kernel and Green's functions for fractional conformal Laplacian.

problem Asymptotics of Poisson kernel and Green's functions for fractional conformal Laplacian.
method Sharp expansions derived for the Poisson kernel and Green's functions near singularities.
result Sharp expansions of the Green's functions solve the first part of Kim-Musso-Wei's conjecture.

We consider the asymptotic expansion of the heat kernel of a generalized Laplacian for t0+t\to 0^+ and characterize the coefficients aka_k of this expansion by a natural intertwining property. In particular we will give a closed formula for the infinite order jet of these coefficients on the diagonal in terms of the loc…

2001-05-17abs ↗pdf ↗

Study Bergman kernels for Gevrey potentials on Kähler manifolds.

problem Analyzing the asymptotic behavior of Bergman kernels for potentials with Gevrey regularity.
method Using the method of \cite{BBS} to find upper bounds for Bergman coefficients.
result Improved asymptotic expansion for Bergman kernels in shrinking neighborhoods of the diagonal.

Analytic Kähler potentials yield analytic Bergman kernels.

problem Characterizing Bergman kernels for analytic Kähler potentials.
method Linear recursive formula for Bergman kernel coefficients, simplified from Charles's work.
result Bergman kernels are analytic symbols with phase determined by Kähler potential polarization.

The paper studies asymptotic expansions of operators related to Bochner-Schrödinger on Riemannian manifolds.

problem Asymptotic expansions of operators related to Bochner-Schrödinger on Riemannian manifolds.
method Analyzes the Bochner-Schrödinger operator HpH_p and its function φ(Hp)\varphi(H_p) in L2(X,LpE)L^2(X,L^p\otimes E), providing an asymptotic expansion of its smooth Schwartz kernel.
result The trace of the operator φ(Hp)\varphi(H_p) admits a complete asymptotic expansion in powers of p1/2p^{-1/2} as pop o \infty.