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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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81162243324 · Jun 202019922001200920172026
48 results for Spherical Designs

New Fourier features improve high-precision approximation in large-scale problems.

problem Designing scalable, high-precision Fourier features for large-scale kernel methods.
method Introducing a new family of quadrature rules that accurately approximate the Gaussian measure in higher dimensions.
result Improved approximation bounds with new Fourier features.

A Steiner chain of length k consists of k circles, tangent to two given non-intersecting circles (the parent circles) and tangent to each other in a cyclic pattern. The Steiner porism states that once a chain of k circles exists, there exists a 1-parameter family of such chains with the same parent circles that can be …

2018-11-20abs ↗pdf ↗

DeepSphere improves spherical CNNs by balancing efficiency and rotation equivariance.

problem Designing efficient and rotation-equivariant convolutional layers for spherical data.
method Graph-based approach to represent spherical data, focusing on the number of vertices and neighbors.
result DeepSphere achieves state-of-the-art performance and demonstrates efficiency and flexibility.

Derives TAP approximation for Bayesian linear regression.

problem Log-normalizing constant of posterior distribution in high-dimensional linear regression.
method Variational representation and Thouless-Anderson-Palmer approximation.
result Proves TAP approximation for spherical prior in proportional asymptotic regime.

Designs neural networks on matrix manifolds for improved performance in tasks like human action recognition.

problem Designing neural networks for tasks on non-Euclidean manifolds.
method Develops fully-connected and convolutional layers for SPD manifolds, and MLR on SPSD manifolds.
result Demonstrates improved performance in human action recognition and node classification tasks.

The paper shows how to use hyperplanes and hyperballs interchangeably using inversive geometry.

problem Tackles the interchangeability of hyperplanes and hyperballs in discriminative boundaries.
method Applies inversive geometry to transform Euclidean data into spherical data and back, providing explicit formulae.
result Shows a duality between hyperspherical caps and hyperballs, providing explicit formulae to map between them.

Six quaternionic lines with optimal angles found in 2D quaternion space.

problem Finding optimal configurations of quaternionic lines in 2D space.
method Simple presentation of lines as orbit of a reflection group, finding other optimal designs.
result Optimal spherical designs of 10, 15, and 20 lines in quaternion space.

Bayesian framework for sphere regression using Gaussian fields.

problem Nonparametric regression on the sphere with Gaussian priors.
method Isotropic Gaussian field priors, harmonic structure, exact posterior distributions, optimal spectral truncation, posterior contraction rates.
result Sharp posterior contraction rates for Gaussian priors with polynomially decaying angular power spectra.

SRCA reduces high-dimensional data to lower dimensions while preserving geometric structures.

problem High-dimensional datasets with underlying geometric structures.
method Spherical Rotation Component Analysis (SRCA) incorporating geometric loss functions.
result SRCA provides a low-rank spherical representation of data with general theoretic guarantees.

Study on naked singularities without symmetry, forming incomplete future null infinity and singular inner Cauchy horizon.

problem Formation of naked singularities in Einstein-scalar field system without symmetry assumptions.
method Employing four-type differences and scale-invariant weighted norms to control geometry.
result Global naked singularity structure with incomplete future null infinity and singular inner Cauchy horizon.

Lower bounds show learning mixtures of linear classifiers is nearly impossible.

problem Learning mixtures of linear classifiers under Gaussian covariates.
method Statistical Query (SQ) lower bounds and new spherical designs.
result Complexity of any SQ algorithm is \( n^{\mathrm{poly}(1/Δ) \log(r)} \), where Δ is the pairwise \(\ell_2\)-separation.

The abstract proves spherical surface decompositions with conical singularities.

problem Decomposing surfaces with spherical metrics and conical singularities.
method Geometric triangulations and irreducible components of standard shapes.
result Spherical polygons, including half-spherical concave polygons, can be arbitrarily complicated.

In this paper we consider the problem of transmitting a continuous alphabet discrete-time source over an AWGN channel. The design of good curves for this purpose relies on geometrical properties of spherical codes and projections of NN-dimensional lattices. We propose a constructive scheme based on a set of curves on …

2012-02-09abs ↗pdf ↗

Study spherical curves with curvature dependent on distance to a great circle.

problem Understanding spherical curves with curvature dependent on distance to a great circle.
method Introducing spherical angular momentum, characterizing known curves, finding new families, and obtaining arc length parametrizations.
result New families of spherical curves with intrinsic equations in elementary or Jacobi elliptic functions.

Study calculates eigenvalues and eigenfunctions for spherical triangles and finds fundamental gap behavior.

problem Understanding eigenvalues and gaps in spherical triangles.
method Explicit computation of Dirichlet eigenvalues and eigenfunctions for spherical lunes and triangles.
result Fundamental gap of spherical triangles increases as the angle of the lune decreases.

Existence and uniqueness of spherical helicoidal surfaces in 3-sphere via spherical curves.

problem Existence and uniqueness of spherical helicoidal surfaces in 3-sphere.
method Continuous function of distance to axis, spherical angular momentum of spherical curves.
result Existence and uniqueness theorem for spherical helicoidal surfaces in 3-sphere.

The reductivity of a spherical curve represents how reduced the spherical curve is. It is unknown if there exists a spherical curve whose reductivity is four. In this paper we give an unavoidable set for spherical curves with reductivity four by considering 4-gons.

2016-03-25abs ↗pdf ↗

The paper improves inequalities for nearly spherical sets using quermassintegrals.

problem Improving inequalities for nearly spherical sets.
method Establishing quantitative Alexandrov-Fenchel inequalities for quermassintegrals.
result Lower bounds on the (k,m)(k,m)-isoperimetric deficit found using spherical deviation and asymmetry.

The reductivity of a spherical curve is the minimal number of a local transformation called an inverse-half-twisted splice required to obtain a reducible spherical curve from the spherical curve. It is unknown if there exists a spherical curve whose reductivity is four. In this paper, an unavoidable set of configuratio…

2017-05-06abs ↗pdf ↗

We show that we can obtain a reducible spherical curve from any non-trivial spherical curve by four or less inverse-half-twisted splices, i.e., the reductivity, which represents how reduced a spherical curve is, is four or less. We also discuss unavoidable sets of tangles for spherical curves.

2014-01-16abs ↗pdf ↗

The paper classifies Landsberg spherically symmetric Finsler metrics in various dimensions.

problem Investigating compatibility conditions on spherically symmetric Finsler metrics.
method Using the inverse problem of calculus of variations, the paper focuses on Landsberg and Berwald types.
result All Landsberg spherically symmetric manifolds in higher dimensions are either Riemannian or have specific geodesic spray formulas.

For a convex body on the Euclidean unit sphere the spherical convex floating body is introduced. The asymptotic behavior of the volume difference of a spherical convex body and its spherical floating body is investigated. This gives rise to a new spherical area measure, the floating area. Remarkably, this floating area…

2014-11-27abs ↗pdf ↗

The paper examines properties of spherical Finsler metrics, proving their semi-C-reducibility and conditions for vanishing mean stretch curvature.

problem Analyzing curvature properties of spherical Finsler metrics.
method Proving semi-C-reducibility and finding conditions for vanishing mean stretch curvature.
result Conditions for a general spherically symmetric Finsler metric to have vanishing mean stretch curvature.

The paper classifies spherically symmetric Finsler metrics as Berwaldian or Riemannian.

problem Classifying spherically symmetric Finsler metrics.
method Proving all spherically symmetric Landsberg surfaces are Berwaldian and modifying the classification of spherically symmetric Finsler metrics.
result All Berwald spherically symmetric metrics of dimension n3n\geq 3 are Riemannian or given by a specific formula.

The paper characterizes spherically symmetric metrics with scalar curvature.

problem Characterizing spherically symmetric metrics with scalar curvature.
method Established a curvature compatibility condition on spherically symmetric Finsler metrics and constructed a Berwald frame.
result Characterized spherically symmetric metrics with scalar curvature.

A spherical polyhedron surface is a triangulated surface obtained by isometric gluing of spherical triangles. For instance, the boundary of a generic convex polytope in the 3-sphere is a spherical polyhedron surface. This paper investigates these surfaces from the point of view of inner angles. A rigidity result is obt…

2004-08-09abs ↗pdf ↗

Kähler-Ricci flow on spherical Fano manifolds converges to a soliton.

problem Analyzing the behavior of Kähler-Ricci flow on spherical Fano manifolds.
method Gromov-Hausdorff limit and torus degeneration.
result The limit of Kähler-Ricci flow on spherical Fano manifolds is a spherical Fano variety with a Kähler-Ricci soliton.

In earlier papers, we introduced spherical T-duality, which relates pairs of the form (P,H)(P,H) consisting of an oriented S3S^3-bundle PMP\rightarrow M and a 7-cocycle HH on PP called the 7-flux. Intuitively, the spherical T-dual is another such pair (P^,H^)(\hat P, \hat H) and spherical T-duality exchanges the 7-flux with …

2015-02-16abs ↗pdf ↗

We introduce spherical T-duality, which relates pairs of the form (P,H)(P,H) consisting of a principal SU(2)SU(2)-bundle PMP\rightarrow M and a 7-cocycle HH on PP. Intuitively spherical T-duality exchanges HH with the second Chern class c2(P)c_2(P). Unless dim(M)4dim(M)\leq 4, not all pairs admit spherical T-duals and the spheric…

2014-05-22abs ↗pdf ↗

DELIMIT is a framework extension for deep learning in diffusion imaging, which extends the basic framework PyTorch towards spherical signals. Based on several novel layers, deep learning can be applied to spherical diffusion imaging data in a very convenient way. First, two spherical harmonic interpolation layers are a…

2018-08-04abs ↗pdf ↗