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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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7132026 · Sep 201919922001200920172026
48 results for geographical distortions

Tissot's indicatrix theory is foundational for quasiconformal mappings.

problem Understanding map distortions in geographical projections.
method Mathematical analysis of map projections and their distortions.
result Tissot's work laid the groundwork for quasiconformal mappings.

2020 Census uses more noise to protect privacy than needed, improving data accuracy.

problem Ensuring privacy in census data while maintaining accuracy for policy decisions.
method Applied ff-differential privacy to track and reduce noise across geographical levels.
result The 2020 Census provides stronger privacy protections than its nominal guarantees suggest.

Euler and Delisle developed a map method for the Russian Empire, which is now outperformed by the Lambert conformal conical projection.

problem Mapping a country onto a flat map while minimizing distortion.
method Developed a heuristic method for mapping the Russian Empire, which was later named Delisle--Euler map.
result The Lambert conformal conical projection outperforms the Delisle--Euler map in several respects.

Study improves motor insurance claim prediction using geographic data.

problem Limited location identifiers in public actuarial datasets.
method Zone-level modeling framework with environmental and orthoimagery data.
result Geographic information improves MTPL claim prediction accuracy.

GWRBoost improves GWR for better spatial relationship quantification.

problem Underfitting in GWR for complex data and lack of explainable quantification.
method Geographically weighted gradient boosting model using localized additive model and gradient boosting optimization.
result Significant improvement in RMSE and AICc compared to classic GWR.

STICC clusters geographic objects considering both spatial contiguity and attributes.

problem Discovering repeated geographic patterns with spatial contiguity.
method Spatial Toeplitz Inverse Covariance-Based Clustering (STICC) method.
result STICC significantly outperforms baseline methods in adjusted rand index and macro-F1 score.

Study uses trajectory embedding to measure place function similarity at fine spatial granularity.

problem Measuring place function similarity at fine spatial granularity.
method Trajectory embedding to reduce dimensions and measure similarity of place functions.
result Embedding similarity can be a metric proxy for place functions at fine spatial granularity.

We consider the problem of distortion minimal morphing of nn-dimensional compact connected oriented smooth manifolds without boundary embedded in Rn+1\R^{n+1}. Distortion involves bending and stretching. In this paper, minimal distortion (with respect to stretching) is defined as the infinitesimal relative change in vol…

2006-05-25abs ↗pdf ↗

This paper shows how to calculate risk measures for sums of two counter-monotonic risks.

problem Calculating risk measures for sums of two counter-monotonic risks.
method Using a fixed distortion function and expressing the risk measure of a sum as the sum of two related measures of the marginals.
result The risk measure of a sum of two counter-monotonic risks can be expressed as the sum of two related distortion risk measures of the marginals.

Algorithm selects variables and bandwidths for geographically weighted regression.

problem Estimating variable subsets and bandwidths for geographically weighted regression.
method Mathematical programming-based approach integrating variable selection and bandwidth estimation.
result Proposed algorithm provides stable spatially varying patterns with competitive explanatory power.

Most distortion correction methods focus on simple forms of distortion, such as radial or linear distortions. These works undistort images either based on measurements in the presence of a calibration grid, or use multiple views to find point correspondences and predict distortion parameters. When possible distortions …

2019-11-15abs ↗pdf ↗

SXL embeds spatial autocorrelation into neural networks for better geographic data learning.

problem Difficulties in learning spatial effects for neural networks in geographic data.
method SXL uses auxiliary tasks and autoregressive embeddings to learn spatial autocorrelation.
result SXL improves neural network training in unsupervised and supervised learning tasks.

The distortion of a curve measures the maximum arc/chord length ratio. Gromov showed any closed curve has distortion at least pi/2 and asked about the distortion of knots. Here, we prove that any nontrivial tame knot has distortion at least 5pi/3; examples show that distortion under 7.16 suffices to build a trefoil kno…

2004-09-22abs ↗pdf ↗

Study reveals centralization in Bitcoin transactions involving retail users.

problem Centralization and bias in Bitcoin transaction data.
method Heuristic classification of Bitcoin users, weekly activity pattern analysis.
result Most real transactions involve Frequent Receivers, centralizing the ecosystem.

New method generates geolocated synthetic populations from real data.

problem Generating synthetic populations with explicit geographic coordinates.
method Mapping coordinates into a latent space using Normalizing Flows (NF), then combining with other features in a Variational Autoencoder (VAE).
result NF+VAE architecture outperforms existing methods in generating geolocated synthetic populations.

The objective of this paper is to fill a gap in the literature on internationalization, in relation to the absence of objective and measurable performance indicators on the process of how firms sequentially enter external markets. To that end, this research develops a quantitative tool that can be used as a performance…

2017-10-10abs ↗pdf ↗

Study on risk measures using distorted Choquet integrals with random distortions.

problem Developing risk measures under random distortions of capacities.
method Introducing and analyzing randomly distorted Choquet integrals with respect to a distorted capacity, establishing properties and providing representations.
result Representation of comonotonic additive conditional risk measures using G-randomly distorted Choquet integrals.

Proposes FSM-IRL to learn invariant network representations considering feature and structural shifts.

problem Spatial heterogeneity and temporal dynamics lead to OOD generalization issues in geographic networks.
method Introduces FSM-IRL model that accounts for feature and structural distribution shifts using causal attention and reweighting.
result Demonstrates strong learning capabilities on geographic and social network datasets in OOD scenarios.

We show that an entire branched cover of finite distortion cannot have a compact branch set if its distortion satisfies a certain asymptotic growth condition. We furthermore show that this bound is strict by constructing an entire, continuous, open and discrete mapping of finite distortion which is piecewise smooth, ha…

2017-09-25abs ↗pdf ↗

The study shows exponential distortion in virtually special groups containing free subgroups.

problem Understanding distortion in virtually special groups containing free subgroups.
method Constructing examples of virtually special groups with finite rank free subgroups.
result Distortion functions grow like exp^k(x^m) and can be superexponential.

Estimates rate-distortion function for large datasets using neural networks.

problem Designing lossy data compression schemes and comparing them with theoretical limits.
method Re-formulate rate-distortion objective and solve using neural networks.
result NERD accurately estimates the rate-distortion function for real-world datasets.

Paper proposes a new black-box attack approach to minimize visual distortion.

problem Constructing adversarial examples that minimize visual distortion in a black-box threat model.
method Learning the noise distribution of adversarial examples to approximate the gradient of a non-differentiable loss function.
result The proposed attack results in much lower visual distortion compared to state-of-the-art black-box attacks.

Study dynamic risk measures and performance indices using distortion functions.

problem Investigate time consistency of dynamic risk measures and performance indices generated by distortion functions.
method Analyze dynamic coherent risk measures (DCRMs) and dynamic weighted value at risk measures, proving their equivalence. Establish properties of families of DCRMs generated by distortion functions and define corresponding dynamic coherent acceptability indices (DCAIs). Examine time consistency of DCRMs and DCAIs.
result DCRM generated by distortion functions are sub-martingale time consistent but not super-martingale time consistent and not weakly acceptance time consistent.

In this paper, we compute the subgroup distortion of all finitely generated subgroups of all finitely generated 3-manifold groups, and the subgroup distortion in this case can only be linear, quadratic, exponential and double exponential. It turns out that the subgroup distortion of a subgroup of a 3-manifold group is …

2019-04-28abs ↗pdf ↗

The problem behind this paper is the proper measurement of the degree of quality/acceptability/distance to arbitrage of trades. We are narrowing the class of coherent acceptability indices introduced by Cherny and Madan (2007) by imposing an additional mathematical property. For this, we introduce the notion of a conca…

2011-04-04abs ↗pdf ↗