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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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285683111 · May 202619922001200920172026
48 results for pointwise density

The paper analyzes how the one-dimensional Wasserstein distance captures pointwise density differences in finite samples.

problem Uncertainty in identifying density differences when supports overlap and densities have substantial pointwise differences.
method Analysis using the Poisson process and neural spike train decoding.
result The one-dimensional Wasserstein distance highlights meaningful density differences related to both rate and support.

In recent years, kernel density estimation has been exploited by computer scientists to model machine learning problems. The kernel density estimation based approaches are of interest due to the low time complexity of either O(n) or O(n*log(n)) for constructing a classifier, where n is the number of sampling instances.…

2007-09-18abs ↗pdf ↗

Bayesian inference engines improve density estimation accuracy and scalability.

problem Constructing accurate and scalable probability density functions.
method Bayesian inference engines (no-U-turn sampling and expectation propagation) with binning strategy.
result Density estimates have excellent comparative performance and scale well to large sample sizes.

Interactive privacy mechanisms improve spectral density estimation under local differential privacy.

problem Estimating spectral density of Gaussian time series with local differential privacy constraints.
method Two-stage process: Laplace mechanism followed by privatized sample analysis.
result Interactive mechanisms achieve faster rates for spectral density estimation.

This article proposes a novel density estimation based algorithm for carrying out supervised machine learning. The proposed algorithm features O(n) time complexity for generating a classifier, where n is the number of sampling instances in the training dataset. This feature is highly desirable in contemporary applicati…

2007-10-31abs ↗pdf ↗

Study on regularity of optimal transport maps on convex domains with quadratic cost.

problem Regularity of optimal transport maps between convex domains with quadratic cost.
method Analysis of CαC^α-densities and C1,αC^{1, α} boundary conditions, monotonicity formula for optimal transport maps.
result Proves C1,1εC^{1, 1-\varepsilon}-regularity for nondegenerate CαC^α-densities and C2,αC^{2, α}-regularity for C1,αC^{1, α} boundary.

Robustly infers manifold density and geometry under high-dimensional noise.

problem Inaccurate kernel density estimation under high-dimensional noise.
method Doubly stochastic normalization of Gaussian kernel.
result Robust tools for density estimation, noise magnitude estimation, and distance approximation.

We propose a natural definition of the weighted σkσ_k-curvature for a manifold with density; i.e.\ a triple (Mn,g,eφdvol)(M^n,g,e^{-φ}\mathrm{dvol}). This definition is intended to capture the key properties of the σkσ_k-curvatures in conformal geometry with the role of pointwise conformal changes of the metric replaced by pointw…

2014-09-15abs ↗pdf ↗

Proves well-posedness for Einstein equations with specific boundary conditions.

problem Well-posedness of vacuum Einstein equations with twisted Dirichlet boundary conditions.
method Proves local-in-time well-posedness for the IBVP of the Einstein equations with specified conformal class and scalar densities.
result Proves well-posedness for the Einstein equations with twisted Dirichlet boundary conditions.

Study minimax robustness in statistical estimation under Wasserstein contamination.

problem Adversarial perturbations in statistical data.
method Developed minimax theory for qr\ell_q^r losses under Wasserstein-rr contaminations.
result Exact minimax risk identified for joint contaminations in location estimation and prediction in linear regression.

EagleEye detects localized density anomalies in multivariate data.

problem Identifying signal events, regime changes, or model mismatch in scientific data.
method EagleEye pinpoints local over- and under-densities by assigning anomaly scores based on binary membership sequences and binomial null models.
result EagleEye can detect genuine local anomalies and estimate background purity.

This paper provides a neural approach to represent option implied information.

problem Link between implied density and volatility for arbitrage-free modeling.
method Minimalist perspective on implied volatility, neural representation with arbitrage constraints.
result Shallow feedforward network with a single hidden layer effectively approximates implied density and volatility.

The paper analyzes Laplace learning for Gaussian measure data in infinite dimensions, proving convergence.

problem Analyzing Laplace learning for infinite-dimensional Gaussian measure data.
method Minimizes Dirichlet energy on a graph constructed from the full dataset.
result Proves pointwise convergence of the graph Dirichlet energy for Gaussian measure data.

FourNet approximates financial transition densities using Fourier transforms.

problem Approximating transition densities in finance with high accuracy.
method FourNet is a novel FFNN with Gaussian activation, learning from characteristic functions.
result FourNet can approximate transition densities arbitrarily well with finite neurons.

Given a compact manifold NnRνN^n \subset \mathbb{R}^ν, s1s \ge 1 and 1p<1 \le p < \infty, we prove that the class of smooth maps on the cube with values into NnN^n is strongly dense in the fractional Sobolev space Ws,p(Qm;Nn)W^{s, p}(Q^m; N^n) when NnN^n is sp\lfloor sp \rfloor simply connected. For spsp integer, we prove weak den…

2012-10-09abs ↗pdf ↗

Developed a monotone numerical method for MV portfolio optimization under jump-diffusion models.

problem Efficiently optimizing portfolios with jump-diffusion dynamics and investment constraints.
method Strictly monotone numerical integration method using Fourier transforms and composite quadrature rules.
result Proven to be \ell_{\infty}-stable and pointwise consistent, converging to the MV optimization solution.

We introduce the notions of pointwise almost h-slant submanifolds and pointwise almost h-semi-slant submanifolds as a generalization of slant submanifolds, pointwise slant submanifolds, semi-slant submanifolds, and pointwise semi-slant submanifolds. We have characterizations and investigate the integrability of distrib…

2013-12-12abs ↗pdf ↗

Study properties of pointwise k-slant submanifolds in Kähler manifolds.

problem Characterize the integrability of component distributions in Kähler manifolds.
method Characterization through integrability and totally geodesic cases.
result Characterize the integrability of component distributions in Kähler manifolds.

The paper studies a new type of submanifolds in product spaces.

problem Characterizing and understanding warped product pointwise bi-slant submanifolds.
method Introduced and studied warped product pointwise bi-slant submanifolds of locally product Riemannian manifolds.
result Characterization results and non-trivial examples of these submanifolds.

Study on slant submanifolds with new conditions and transitivity.

problem Conditions for slant submanifolds under different structures.
method Analyzes pointwise slant submanifolds under two anti-commuting almost Hermitian structures and their transitivity.
result Property of being pointwise slant is transitive on a class of proper pointwise slant immersed submanifolds.

In this paper we contribute a novel algorithm family, which generalizes many unsupervised techniques including unnormalized and energy models, and allows us to infer different statistical modalities (e.g. data likelihood and ratio between densities) from data samples. The proposed unsupervised technique, named Probabil…

2019-03-25abs ↗pdf ↗

The paper studies geometric properties of a specific type of submanifolds in Kaehler manifolds.

problem Analyzing the geometry of pointwise semi-slant warped products in locally conformal Kaehler manifolds.
method The study extends Chen's inequality for CR-warped product submanifolds and investigates equality cases.
result Several results extend Chen's inequality for CR-warped product submanifolds in Kaehler manifolds.

In this paper we study general rotational surfaces in the 4- dimensional Euclidean space E4 and give a characterization of flat general rotation surface with pointwise 1-type Gauss map. Also, we show that a non-planar flat general rotation surface with pointwise 1-type Gauss map is a Lie group if and only if it is a Cl…

2013-02-12abs ↗pdf ↗

Study bounds derivatives of solutions to a specific equation on domains.

problem Bounding second derivatives of solutions to the σkσ_k-Yamabe equation.
method Proves local pointwise second derivative estimates for positive W2,pW^{2,p} solutions.
result Establishes bounds for derivatives of solutions to the σkσ_k-Yamabe equation.

Paper introduces second-order Esscher densities for continuous-time models.

problem Modeling continuous-time market models with second-order Esscher densities.
method Introduced linear and exponential classes of second-order Esscher densities, characterized using semimartingale characteristics and pointwise equations.
result Characterized the relationship between linear and exponential classes for one-dimensional case and showed their connection in compound Poisson and jump-diffusion models.

Our goal in this paper is to develop an effective estimator of fractal dimension. We survey existing ideas in dimension estimation, with a focus on the currently popular method of Grassberger and Procaccia for the estimation of correlation dimension. There are two major difficulties in estimation based on this method. …

2013-12-09abs ↗pdf ↗

An affine hypersurface MM is said to admit a pointwise symmetry, if there exists a subgroup GG of Aut(TpM){\rm Aut}(T_p M) for all pMp\in M, which preserves (pointwise) the affine metric hh, the difference tensor KK and the affine shape operator SS. Here, we consider 3-dimensional indefinite affine hyperspheres, i.e. $S…

2009-10-19abs ↗pdf ↗

It is known that there exist no warped product semi-slant submanifolds in Kaehler manifolds \cite{Sahin}. Recently, Chen and Garay studied pointwise-slant submanifolds of almost Hermitian manifolds in \cite{CG} and obtained many new results for such submanifolds. In this paper, we first introduce pointwise semi-slant s…

2013-10-10abs ↗pdf ↗

Researchers develop neural networks for approximating functions in Banach spaces.

problem Approximating Banach space valued continuous functions.
method Quasi-interpolation Banach space valued neural network operators using algebraic sigmoid functions.
result Jackson type inequalities for function approximation.

Paper provides estimates for varifolds with critical mean curvature.

problem Estimating tilt-excess on varifolds with critical mean curvature.
method Generalizing Lipschitz approximation and Sobolev-Poincaré estimates to almost-integral rectifiable varifolds.
result VMO-type estimates for quadratic tilt-excess on varifolds with critical mean curvature.