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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.

168,657 papers · 148 categories

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168337505673 · Jun 202019922001200920172026
48 results for small area estimation

Random forests and LASSO methods improve small area estimation using auxiliary data.

problem Estimating household consumption in small areas with limited sampled data.
method Model-based small area estimation using random forests and LASSO with auxiliary information.
result Bayesian shrinkage performed best in terms of bias, MSE, and prediction interval coverages.

Horseshoe priors improve small area estimation by borrowing strength globally but locally.

problem Improving precision of small area estimators through global-local borrowing of strength.
method Developed a tail-robust horseshoe model for Fay-Herriot small area estimation, using heteroscedastic Tweedie identity and regular variation theory.
result The horseshoe model outperforms structured Gaussian smoothing on strongly spatial data, identifying exceptional areas that smoothing suppresses.

PriorVAE uses VAEs to efficiently encode spatial priors for small-area estimation.

problem Efficiently encoding spatial priors for small-area estimation using Gaussian processes.
method Approximating Gaussian process priors with a variational autoencoder (VAE).
result Efficient spatial inference through a low-dimensional latent Gaussian space representation.

Differential privacy for simple linear regression protects small datasets from individual data leaks.

problem Protecting sensitive personal information in small datasets from individual data leaks.
method Differential privacy algorithms for simple linear regression tailored for small datasets (tens to hundreds of datapoints).
result Robust estimators like Theil-Sen perform well on small datasets, but standard algorithms improve as dataset size increases.

We show the existence of a smooth spherical surface minimizing the Willmore functional subject to an area constraint in a compact Riemannian three-manifold, provided the area is small enough. Moreover, we classify complete surfaces of Willmore type with positive mean curvature in Riemannian three-manifolds.

2012-01-09abs ↗pdf ↗

We investigate the Hawking energy of small surfaces in space times without symmetry assumptions by introducing the notion of Hawking type functionals. In particular, we find that Hawking type functionals are generalized Willmore functionals which allows us to find area constrained, minimizing, immersed, haunted bubble …

2019-09-05abs ↗pdf ↗

TLRF improves timely COVID-19 outbreak detection with small sample size counties.

problem Balancing accuracy and speed in estimating COVID-19 case growth rates.
method Transfer Learning Random Forest (TLRF) framework for growth rate estimation.
result TLRF outperforms existing methods in predicting case growth rates and timely outbreak detection.

Paper proposes efficient multivariate spatial Fay-Herriot models using variational autoencoders.

problem Estimating population characteristics in small areas with limited data.
method Integrates multivariate spatial Fay-Herriot model with variational autoencoders to leverage spatial structure efficiently.
result Significant computational efficiency improvements for high-dimensional datasets.

Bayesian SAE model with spectral clustering and uncertainty quantification.

problem Small Area Estimation (SAE) with uncertainty quantification.
method Spectral clustering with external covariates, posterior projections, and CPMSE.
result Closed form expressions for posterior mean estimators and CPMSE.

Study on Laplacian determinant in isosceles triangles, finding equilateral triangle minimizes determinant.

problem Finding the minimum of the spectral determinant on isosceles triangles.
method Analyzing the determinant of the Laplacian on Euclidean isosceles triangle envelopes of fixed area.
result Equilateral triangle envelope minimizes the determinant of the Laplacian.

The paper examines partial regularity of Lipschitz solutions to minimal surface system.

problem Understanding the regularity of solutions to the minimal surface system.
method Investigation of stationary, integral weak, and viscosity solutions; interior gradient estimate using maximum principle.
result Partial regularity results for Lipschitz solutions, including interior gradient estimate.

We prove that a strictly stable minimal Ch2C^2_h intrinsic graph G is locally area-minimizing, i.e. given any Ch1C^1_h graph SS with the same boundary, Area(G)<Area(S)\text{Area}(G)<\text{Area}(S) unless G=SG=S. As a consequence we show the existence and the uniqueness of CC^\infty minimal graphs with prescribed small boundary datum…

2017-01-22abs ↗pdf ↗

Our main result is that for all sufficiently large x0>0x_0>0, the set of commensurability classes of arithmetic hyperbolic 2- or 3-orbifolds with fixed invariant trace field kk and systole bounded below by x0x_0 has density one within the set of all commensurability classes of arithmetic hyperbolic 2- or 3-orbifolds wit…

2015-04-20abs ↗pdf ↗

The study examines the index of MOTS in Kerr-Newman-de Sitter spacetime and its relation to mass and charge.

problem Investigating the index of MOTS in Kerr-Newman-de Sitter spacetime.
method Analyzing the spatial cross section of the cosmological horizon in the Kerr-Newman-de Sitter spacetime, proving index bounds and establishing area-charge estimates.
result Established bounds on the index of MOTS and a connection between MOTS with index one and General Relativity.

The paper estimates area and volume for spacetimes with integral mean curvature bounds.

problem Estimating area and volume for spacetimes with specific curvature conditions.
method Using strong energy condition and norms of second fundamental form/mean curvature.
result Established area and volume estimates for spacetimes.

We present a conjecture, based on computational results, on the area minimizing way to enclose and separate two arbitrary volumes in the flat cubic 3-torus. For comparable small volumes, we prove that an area minimizing double bubble in the 3-torus is the standard double bubble from R^3.

2002-08-15abs ↗pdf ↗

New foliations found for critical surfaces of Hawking energy, resolving discrepancies.

problem Finding consistent critical surfaces for the Hawking energy in non-totally geodesic spacelike hypersurfaces.
method Constructing a unique local foliation of area constrained critical surfaces of the Hawking energy in the general case of non-totally geodesic spacelike hypersurfaces.
result Discrepancy found in the small sphere limit of the Hawking energy, explained and resolved.

Study of large area-constrained Willmore surfaces in Schwarzschild-like manifolds.

problem Understanding Willmore surfaces in asymptotically Schwarzschild 3-manifolds.
method Application of Lyapunov-Schmidt reduction method.
result End of the manifold is foliated by area-constrained Willmore spheres.

In [dLMu05], DeLellis and Müller proved a quantitative version of Codazzi's theorem, namely for a smooth embedded surface  ΣR3 \ Σ\subseteq \mathbb{R}^3\ with area normalized to  H2(Σ)=4π\ {\cal H}^2(Σ) = 4 π , it was shown that  AΣidL2(Σ)CAΣ0L2(Σ) \ \parallel A_Σ- id \parallel_{L^2(Σ)} \leq C \parallel A^0_Σ\parallel_{L^2(Σ)}\ , and building on…

2013-10-18abs ↗pdf ↗

Efficiently tests machine learning models with minimal labeled data.

problem Guaranteeing the performance of machine learning models and preventing failures.
method Proposes a novel framework using Bayesian neural networks and data augmentation for efficient testing.
result Metrics estimations by the proposed method are significantly better than existing baselines.

In many applications, monitoring area under the ROC curve (AUC) in a sliding window over a data stream is a natural way of detecting changes in the system. The drawback is that computing AUC in a sliding window is expensive, especially if the window size is large and the data flow is significant. In this paper we propo…

2019-02-02abs ↗pdf ↗

Proposes a sample-efficient method for uncertainty estimation in deep learning.

problem Inaccurate uncertainty estimation in deep learning models, especially with limited data.
method Probabilistic Neighbourhood Component Analysis (PCA) for sample-efficient uncertainty estimation.
result Demonstrates superior uncertainty quantification compared to state-of-the-art methods.

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.

Estimates area and spectrum of stable minimal surfaces in Euclidean and hyperbolic spaces.

problem Estimating the growth of area and spectrum of stable minimal surfaces.
method Elementary argument and stability inequality for Euclidean space; explicit area growth estimate for hyperbolic space; scalar curvature lower bound for spectrum.
result Minimal surfaces in Euclidean space grow like the Euclidean plane, and in hyperbolic space, explicit area growth estimates are derived.

Motivated by the HRRT-formula for holographic entanglement entropy, we consider the following question: what are the position and the surface area of extremal surfaces in a perturbed geometry, given their anchor on the asymptotic boundary? We derive explicit expressions for the change in position and surface area, ther…

2017-10-03abs ↗pdf ↗

We are interested in the maximum value achieved by the systole function over all complete finite area hyperbolic surfaces of a given signature (g,n)(g,n). This maximum is shown to be strictly increasing in terms of the number of cusps for small values of nn. We also show that this function is greater than a function that…

2012-01-17abs ↗pdf ↗

For appropriately values of HH, we obtain an area estimate for a complete non-compact HH-surface of finite topology and finite area, embedded in a three-manifold of negative curvature. Moreover, in the case of equality and under additional assumptions, we prove that a neighbourhood of the mean convex side of the surf…

2017-06-21abs ↗pdf ↗

Smooth minimizing hypersurfaces in 11D are generic, with singularities in higher dimensions.

problem Finding smooth minimizing hypersurfaces in high dimensions.
method Analyzing the Plateau problem and area minimization in integral homology.
result Smooth minimizing hypersurfaces are generic in 11D, with singularities in higher dimensions.

We study the problem of estimating the parameters of a Gaussian distribution when samples are only shown if they fall in some (unknown) subset SRdS \subseteq \R^d. This core problem in truncated statistics has long history going back to Galton, Lee, Pearson and Fisher. Recent work by Daskalakis et al. (FOCS'18), provide…

2019-08-02abs ↗pdf ↗