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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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3774110147 · May 202619922001200920172026
48 results for uniform decay

Study on Kähler manifolds connects curvature decay with growth of holomorphic functions.

problem Analyzing properties of Kähler manifolds with nonnegative bisectional curvature.
method Established precise relations among minimal degree, volume growth, and scalar curvature decay.
result Unified understanding of Kähler-Ricci flow through polynomial growth holomorphic functions.

Uniform diffusion approximation for SGD in non-convex settings.

problem Finite-time diffusion approximation for SGD.
method Establishing uniform-in-time diffusion approximation with strong convexity and mild conditions.
result Uniform-in-time diffusion approximation of SGD without convexity of each loss function.

The paper proves boundedness and decay of Teukolsky equations on Kerr backgrounds.

problem Analyzing boundedness and decay of Teukolsky equations on Kerr backgrounds.
method Adapting techniques from scalar waves, uniform-in-frequency estimates for Teukolsky PDEs were obtained.
result Solutions of Teukolsky equation on subextremal Kerr backgrounds remain bounded and decay in time.

The paper studies steady solitons with curvature decay and proves their smoothness.

problem Analyzing the properties of steady solitons with curvature decay.
method Bootstrap regularity in harmonic coordinates using the soliton equation.
result Steady gradient Ricci solitons are asymptotically cylindrical under certain curvature decay conditions.

The paper discusses methods to compute Green's function on algebraic surfaces using Schottky uniformization.

problem Computing Green's function on algebraic surfaces using Schottky uniformization.
method Investigates convergence of deformations of a formula related to Green's function.
result Provides insights into the geometric interpretation of the formula for Green's function.

SHIFT framework identifies subgroups with large ML model performance decay.

problem Large model performance decay in subgroups when deployed.
method Subgroup-scanning Hierarchical Inference Framework (SHIFT) for performance drift.
result SHIFT identifies interpretable subgroups with large performance decay and suggests targeted actions to mitigate it.

This paper is motivated by the non-linear stability problem for the expanding region of Kerr de Sitter cosmologies in the context of Einstein's equations with positive cosmological constant. We show that under dynamically realistic assumptions the conformal Weyl curvature of the spacetime decays towards future null inf…

2016-10-13abs ↗pdf ↗

New insights into how to inspect and learn from multi-stage processes and AI reasoning.

problem Understanding how to attribute outcomes to early stages in multi-stage operations and AI reasoning.
method Information-theoretic analysis and mathematical proofs of four key results.
result Uniform checkpoint spacing is minimax-optimal for inspection design under homogeneous signal attenuation.

The authors prove that the logarithmic Monge-Ampère flow with uniformly bound and convex initial data satisfies uniform decay estimates away from time t=0t=0. Then applying the decay estimates, we conclude that every entire classical strictly convex solution of the equation {equation*} \det D^{2}u=\exp\{n(-u+1/2\sum_{i=…

2009-11-15abs ↗pdf ↗

Study on biharmonic heat equation on manifolds with curvature constraints.

problem Analyzing entire solutions of biharmonic heat equation on manifolds.
method Exponential decay estimates for biharmonic heat kernel under Ricci curvature and noncollapsing conditions. Proving uniqueness criteria for Cauchy problem.
result Conservation law for biharmonic heat kernel and uniform L-infinity estimate for entire solutions.

Let (Mn,g)(M^n, g) be a complete non-compact Kähler manifold with non-negative and bounded holomorphic bisectional curvature. We prove that MM is holomorphically covered by a pseudoconvex domain in $\C^n$ which is homeomorphic to R2n\R^{2n}, provided (Mn,g)(M^n, g) has uniform linear average quadratic curvature decay.

2006-10-18abs ↗pdf ↗

The paper analyzes Teukolsky equations on Kerr backgrounds, proving boundedness and decay of solutions.

problem Analyzing boundedness and decay of solutions to Teukolsky equations on Kerr backgrounds.
method Frequency space analysis of transformed Teukolsky equations on Kerr backgrounds.
result Fixed frequency solutions remain bounded and decay in time for subextremal Kerr backgrounds.

We consider solutions to the linear wave equation gφ=0\Box_gφ=0 on a non-extremal maximally extended Schwarzschild-de Sitter spacetime arising from arbitrary smooth initial data prescribed on an arbitrary Cauchy hypersurface. (In particular, no symmetry is assumed on initial data, and the support of the solutions may con…

2007-09-18abs ↗pdf ↗

We construct a sequence of smooth Ricci flows on T2T^2, with standard uniform C/tC/t curvature decay, and with initial metrics converging to the standard flat unit-area square torus g0g_0 in the Gromov-Hausdorff sense, with the property that the flows themselves converge not to the static Ricci flow g(t)g0g(t)\equiv g_0, bu…

2019-04-25abs ↗pdf ↗

We show that under very general assumptions the partial Bergman kernel function of sections vanishing along an analytic hypersurface has exponential decay in a neighborhood of the vanishing locus. Considering an ample line bundle, we obtain a uniform estimate of the Bergman kernel function associated to a singular metr…

2016-01-03abs ↗pdf ↗

This paper examines weight initialization for 1-Lipschitz networks to improve robustness against adversarial attacks.

problem Improving the robustness of deep neural networks against adversarial attacks.
method Examined weight parametrization of AOL and SLL networks, calculated weight variance bounds, and demonstrated weight decay.
result Weight initialization causes deep 1-Lipschitz networks to decay to zero, and weight variance does not affect output variance distribution.

This is the second in a series of papers in which we take a systematic study of gauge field theories such as the Maxwell equations and the Yang-Mills equations, on curved space-times. In this paper, we study the Maxwell equations in the domain of outer-communication of the Schwarzschild black hole. We show that if we a…

2014-09-29abs ↗pdf ↗

This article proves a uniform exponential decay estimate for Seiberg-Witten equations on non-compact 4-manifolds with exact symplectic ends of bounded geometry. This is an extension of the analysis for asymptotically flat almost Kähler (AFAK) structures by Kronheimer and Mrowka. As an application, we construct an invar…

2016-03-26abs ↗pdf ↗

We consider the mean curvature flow of the graph of a smooth map f:R2R2f:\mathbb{R}^2\to\mathbb{R}^2 between two-dimensional Euclidean spaces. If ff satisfies an area-decreasing property, the solution exists for all times and the evolving submanifold stays the graph of an area-decreasing map ftf_t. Further, we prove unifo…

2016-08-18abs ↗pdf ↗

Let NN be a complete manifold with bounded geometry, such that secNσ<0\sec_N\le -σ< 0 for some positive constant σσ. We investigate the mean curvature flow of the graphs of smooth length-decreasing maps f:RmNf:\mathbb{R}^m\to N. In this case, the solution exists for all times and the evolving submanifold stays the graph of a…

2018-05-29abs ↗pdf ↗

We study here numerically the behavior of an ideal gas like model of markets having only one non-consumable commodity. We investigate the behavior of the steady-state distributions of money, commodity and total wealth, as the dynamics of trading or exchange of money and commodity proceeds, with local (in time) fluctuat…

2006-09-08abs ↗pdf ↗

The study examines averages of Laplacian determinants over large genus moduli spaces.

problem Analyzing averages of determinants of Laplacians over large genus moduli spaces.
method Examined the moduli space of hyperbolic surfaces with the Weil-Petersson metric, showing decay rates and approaching constants for specific functions.
result Found a universal constant E and decay rates for expected values of determinants over large genus moduli spaces.

We propose and analyze a variant of the classic Polyak-Ruppert averaging scheme, broadly used in stochastic gradient methods. Rather than a uniform average of the iterates, we consider a weighted average, with weights decaying in a geometric fashion. In the context of linear least squares regression, we show that this …

2018-02-22abs ↗pdf ↗

New height estimate for area minimizing currents, leading to unique tangent cones and decay properties.

problem Analyzing singularities of area minimizing currents.
method Height estimate, decay estimates, techniques inspired by previous works.
result Locally area minimizing currents have a unique tangent cone at almost every point and decay rapidly to a unique tangent plane at branch points.

We prove that finite Morse index solutions to the Allen-Cahn equation in R2\R^2 have {\bf finitely many ends} and {\bf linear energy growth}. The main tool is a {\bf curvature decay estimate} on level sets of these finite Morse index solutions, which in turn is reduced to a problem on the uniform second order regularit…

2017-05-18abs ↗pdf ↗

Language models allocate information storage, not collapsing into uniform representations.

problem Incomplete neural collapse in language model representations.
method Analyzing variance and information sharing across 14 models, proving an information floor.
result Within-class variance is allocated information storage, not collapsed into uniform representations.

New theory sharpens Q-learning with LDTZ rate, proving it's best of both worlds.

problem Improving Q-learning's theoretical and practical performance.
method Developed a sharp non-asymptotic error bound and central limit theory for Q-learning with PD2Z-ν schedule.
result Q-learning with LDTZ schedule achieves rapid decay and asymptotic convergence guarantees.

Autoencoder estimates parameters of noisy, multi-component damped signals.

problem Parameter estimation of damped sinusoidal signals under rapid decay and noise.
method Autoencoder-based approach using latent space for frequency, phase, decay, and amplitude estimation.
result High accuracy in parameter estimation, robustness to subdominant components and phase differences.

In this paper we establish a uniform C2,θC^{2,θ} estimate for level sets of stable solutions to the singularly perturbed Allen-Cahn equation in dimensions n10 n\leq 10 (which is optimal). The proof combines two ingredients: one is the infinite dimensional reduction method which enables us to reduce the C2,θC^{2,θ} estimate …

2018-10-22abs ↗pdf ↗

Uniform bounds for neural networks' generalization error in overparameterized settings.

problem Generalization error in overparameterized neural networks.
method Neural Tangent kernel theory and Mercer decomposition of the NT kernel in spherical harmonics.
result Uniform generalization bounds for overparameterized neural networks in RKHS.

Paper analyzes Langevin dynamics for multimodal Gaussian mixtures, controlling errors across dimensions.

problem Challenges in obtaining stable diffusion-based samplers in high- and infinite-dimensional settings.
method Study of preconditioned Annealed Langevin Dynamics (ALD) for Gaussian mixtures, focusing on Euler-Maruyama (EM) and exponential-integrator schemes.
result Proves dimension-uniform KL bounds for the exponential-integrator scheme, allowing arbitrarily small divergence with dimension.

The study proves stable minimal immersions in positively curved manifolds are totally geodesic.

problem Proving stable minimal immersions in positively curved manifolds are totally geodesic.
method Formulating stable Bernstein type theorems in certain positively curved ambient manifolds.
result Proves stable minimal immersions in positively curved manifolds are totally geodesic.

The study examines how much data is needed for generative and vision-language models to make reliable predictions.

problem Ensuring reliable predictions with low data for models used in medical decision support.
method Analyzes uniform convergence bounds for VLM-induced classifiers under low-dimensional semantic representations.
result Finite-sample uniform convergence bounds for accuracy and calibration functionals of VLM-induced classifiers.