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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.

168,742 papers · 148 categories

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48 results for Laplacian smoothing

Paper finds lower bounds for eigenvalues of Bi-drifted Laplacian on smooth metric measure spaces.

problem Eigenvalue problems for Bi-drifted Laplacian on compact manifolds with boundary conditions.
method Obtained lower bounds using specific curvature conditions.
result Lower bounds for the first eigenvalue of Bi-drifted Laplacian.

In this paper we continue the study of spectral properties of Laplacians associated with an arbitrary smooth distribution on a compact manifold, initiated in a previous paper. Under assumption that the singular foliation generated by the distribution is smooth, we prove that the Laplacian associated with the distributi…

2017-10-27abs ↗pdf ↗

Enhances privacy in federated learning with Laplacian smoothing.

problem Protecting data privacy in federated learning while maintaining model accuracy.
method Laplacian smoothing for differentially private federated learning (DP-Fed-LS).
result Improves model accuracy with differential privacy guarantee and membership privacy.

Smooth solutions up to evolving free boundaries for degenerate equations.

problem Degenerate parabolic equations with evolving free boundaries.
method Smooth short-time existence using linear degenerate equations on a fixed domain.
result Smoothness up to the free boundary for the pp-Laplacian evolution equation and αα-Gauss curvature flow.

Existing approaches to analyzing the asymptotics of graph Laplacians typically assume a well-behaved kernel function with smoothness assumptions. We remove the smoothness assumption and generalize the analysis of graph Laplacians to include previously unstudied graphs including kNN graphs. We also introduce a kernel-fr…

2011-01-28abs ↗pdf ↗

We show that any generalised smooth distribution on a smooth manifold, possibly of non-constant rank, admits a Riemannian metric. Using such a metric, we attach a Laplace operator to any smooth distribution as such. When the underlying manifold is compact, we show that it is essentially self-adjoint. Viewing this Lapla…

2018-07-18abs ↗pdf ↗

For a bounded domain ΩΩ with a piecewise smooth boundary in an nn-dimensional Euclidean space Rn\mathbf{R}^{n}, we study eigenvalues of the Dirichlet eigenvalue problem of the Laplacian. First we give a general inequality for eigenvalues of the Laplacian. As an application, we study lower order eigenvalues of the Lap…

2011-04-28abs ↗pdf ↗

The paper develops bounds and regularity for minimal boundaries in non-smooth spaces with Ricci curvature.

problem Minimal boundaries in non-smooth spaces with Ricci curvature.
method Intrinsic theory of Laplacian bounds, PDE principle, sharp Laplacian bounds on distance function, regularity theory for perimeter-minimizing boundaries.
result Sharp Laplacian bounds and regularity results for perimeter-minimizing boundaries.

Laplacian of distance function shows negative infinity at cut locus points.

problem Understanding the Laplacian of distance functions on Riemannian manifolds.
method Analyzing the Laplacian of the distance function to a point on a smooth Riemannian manifold.
result The Laplacian of the distance function is -\infty at points of the cut locus.

We show that the driving force behind the regularizing effect of Laplacian smoothing on surface elements is the popular mean ratio quality measure. We use these insights to provide natural generalizations to polygons and polyhedra. The corresponding functions measuring the quality of meshes are easily seen to be convex…

2014-06-17abs ↗pdf ↗

Study eigenvalues of p-Laplacian on quaternionic Kähler manifolds.

problem Finding lower bounds for eigenvalues of p-Laplacian on quaternionic Kähler manifolds.
method Analytical proofs for both Neumann and Dirichlet boundary conditions.
result Established lower bounds for eigenvalues on compact quaternionic Kähler manifolds.

Bayesian methods estimate regression functions on submanifolds using graph Laplacian eigenbasis.

problem Estimating regression functions on unknown smooth submanifolds.
method Random geometric graph structure, Bayesian priors based on random basis expansion in graph Laplacian eigenbasis.
result Posterior contraction rates are minimax optimal for any positive smoothness index.

Study uniform convergence of random walk Laplacians to diffusion Laplacian on smooth manifolds.

problem Uniform convergence of random walk Laplacians to diffusion Laplacian on smooth manifolds.
method Analysis of random walks on geometric and directed kNN graphs, using concentration tools and differential geometry.
result Uniform convergence of kkNN Laplacians to diffusion Laplacian, without continuity of transition kernel.

The paper proves gradient estimates for a weighted p-Laplacian equation on Riemannian manifolds.

problem Gradient estimates for a weighted p-Laplacian equation on Riemannian manifolds.
method Assumes a Sobolev inequality and integral Ricci bounds, proving local gradient estimates and Liouville type results.
result Proves local gradient estimates and Liouville type results on manifolds with lower bounds of Ricci curvature.

Recent research connects Hörmander's old work to modern boundary Laplacian analysis.

problem How close is the Dirichlet-to-Neumann map to the boundary Laplacian?
method Investigates techniques from Hörmander's 1950s manuscript to solve modern boundary Laplacian problems.
result Obtained results for DtN maps on non-smooth boundaries, Helmholtz equation, and differential forms.

The p-Laplacian Transformer improves transformer models by assigning higher attention weights to tokens in close proximity.

problem The self-attention mechanism in transformers does not effectively distinguish attention weights between tokens in close and non-close proximity.
method Proposes a novel class of transformers, p-Laplacian Transformers, that use pp-Laplacian regularization to assign higher attention weights to tokens in close proximity.
result Empirically demonstrates that p-Laplacian Transformers outperform baseline transformers on various benchmark datasets.

Let MM be a compact smooth manifold equipped with a positive smooth density μμ and HH be a smooth distribution endowed with a fiberwise inner product gg. We define the Laplacian ΔHΔ_H associated with (H,μ,g)(H,μ,g) and prove that it gives rise to an unbounded self-adjoint operator in L2(M,μ)L^2(M,μ). Then, assuming that HH

2016-06-07abs ↗pdf ↗

Study shows rates for Laplacian-eigenmap methods in nonparametric regression.

problem Minimizing error in nonparametric regression using Laplacian-eigenmap.
method Adaptive and non-adaptive minimax rates using Sobolev space constraints.
result Extends minimax rates to various weighted Laplacian matrices.

This short note aims at (re)proving that the symmetrically normalized graph Laplacian $L=\Id - D^{-1/2}WD^{-1/2}$ (from a graph defined from a Gaussian weighting kernel on a sampled smooth manifold) converges towards the continuous Manifold Laplacian when the sampling become infinitely dense. The convergence rate with …

2011-01-07abs ↗pdf ↗

We study a Laplacian operator related to the characteristic cohomology of a smooth manifold endowed with a distribution. We prove that this Laplacian does not behave very well: it is not hypoelliptic in general and does not respect the bigrading on forms in a complex setting. We also discuss the consequences of these n…

2013-04-17abs ↗pdf ↗

We consider a complete noncompact smooth Riemannian manifold MM with a weighted measure and the associated drifting Laplacian. We demonstrate that whenever the qq-Bakry-Émery Ricci tensor on MM is bounded below, then we can obtain an upper bound estimate for the heat kernel of the drifting Laplacian from the upper b…

2013-04-11abs ↗pdf ↗

Develops method for learning signed graphs from smooth signals.

problem Learning signed graphs from observed data, especially in contexts with both positive and negative interactions.
method Uses net Laplacian as graph shift operator and minimizes total variation of observed signals with ADMM.
result Theoretical proofs of convergence and estimation error bound provided.

Let φ(t),t[0,T]\varphi(t), t\in [0,T] be a smooth solution to the Laplacian flow for closed G_2 structures on a compact 7-manifold MM. We show that for each fixed positive time t(0,T]t\in (0,T], (M,φ(t),g(t))(M,\varphi(t),g(t)) is real analytic, where g(t)g(t) is the metric induced by φ(t)\varphi(t). Consequently, any Laplacian soliton is real a…

2016-01-17abs ↗pdf ↗

For a bounded domain ΩΩ with a piecewise smooth boundary in a complete Riemannian manifold MM, we study eigenvalues of the Dirichlet eigenvalue problem of the Laplacian. By making use of a fact that eigenfunctions form an orthonormal basis of L2(Ω)L^2(Ω) in place of the Rayleigh-Ritz formula, we obtain inequalities for …

2011-04-26abs ↗pdf ↗

Study of intrinsic sub-Laplacian for hypersurfaces in contact sub-Riemannian manifolds.

problem Characterizing the intrinsic sub-Laplacian for hypersurfaces in contact sub-Riemannian manifolds.
method Construction and analysis of the intrinsic sub-Laplacian using Riemannian approximations and stochastic processes.
result The intrinsic sub-Laplacian is stochastically complete, ensuring the process does not hit characteristic points.

GS-B3^3SE improves label shift estimation by smoothing priors on a graph.

problem Label shift adaptation when source and target distributions share conditional but not marginal probabilities.
method Graph-Smoothed Bayesian Black-Box Shift Estimator (GS-B3^3SE) places Laplacian-Gaussian priors on log-priors and confusion-matrix columns tied by a label-similarity graph.
result GS-B3^3SE produces a tractable posterior with HMC or Newton-CG schemes, proving identifiability, contraction, and robustness.

The paper analyzes thin-shell limits for viscous operators on Riemannian hypersurfaces.

problem Analyzing boundary conditions and thin-shell limits for viscous operators on arbitrary smooth hypersurfaces.
method Decomposing the ambient Bochner Laplacian into intrinsic and radial pieces, proving results for stress-free and Hodge boundary conditions.
result Universal thin-shell limits for viscous operators on arbitrary smooth hypersurfaces, including stress-free and Hodge boundary conditions.

The paper analyzes graph Laplacians on manifolds with curvature bounds and applies to non-collapsed spaces.

problem Analyzing spectral properties of graph Laplacians on manifolds with curvature constraints.
method Quantitative bounds on eigenvalues and eigenfunctions of graph Laplacians constructed from random variables on manifolds with uniform lower Ricci curvature bounds.
result Spectral convergence of graph Laplacians on manifolds with curvature bounds and in non-collapsed spaces.