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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.

169,042 papers · 148 categories

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115230344459 · Jun 202019922001200920172026
48 results for second order rectifiability

Rectifiable varifolds with bounded curvature can be covered by smooth surfaces.

problem Understanding the structure of rectifiable varifolds with bounded curvature.
method Using curvature of arbitrary closed sets and viscosity solutions of PDEs.
result The support of rectifiable varifolds can be covered by smooth submanifolds.

Study introduces weak elastic energy for curves on Riemannian surfaces.

problem Detecting curvature of curves on Riemannian surfaces.
method Relaxation starting from inscribed geodesic polygonals, defined in normalized isothermal coordinates.
result Relaxed energy detects intrinsic second-order Sobolev regularity and agrees with geodesic curvature.

Harmonic maps to Euclidean buildings have rectifiable singular strata.

problem Understanding the structure of singular points for harmonic maps.
method Defining singular strata and proving rectifiability using the rectifiable Reifenberg program.
result Rectifiability of singular strata for harmonic maps into FF-connected complexes.

We prove (without using Federer's structure theorem) that a finite-mass flat chain over any coefficient group is rectifiable if and only if almost all of its 0-dimensional slices are rectifiable. This implies that every flat chain of finite mass and finite size is rectifiable. It also leads to a simple necessary and su…

1999-07-01abs ↗pdf ↗

Rectified flows achieve optimal sample complexity for generating data.

problem Generating high-quality data samples efficiently.
method Rectified flows constrain transport trajectories to be linear, enabling efficient sampling.
result Achieve sample complexity of ildeO(ε2) ilde{O}(\varepsilon^{-2}), matching optimal rate for mean estimation.

In Heisenberg groups, rectifiability is studied for subsets using C1,αC^{1,α}-regular surfaces.

problem Understanding rectifiability of subsets in Heisenberg groups.
method Introducing a new notion of rectifiability and proving conditions for rectifiability using tangent paraboloids.
result A sufficient condition for C1,αC^{1,α}-rectifiability of low-codimensional subsets in Heisenberg groups is the existence of suitable approximate tangent paraboloids.

We propose convex relaxations for convolutional neural nets with one hidden layer where the output weights are fixed. For convex activation functions such as rectified linear units, the relaxations are convex second order cone programs which can be solved very efficiently. We prove that the relaxation recovers the glob…

2018-12-31abs ↗pdf ↗

The paper explores rectified flows and their relation to optimal transport.

problem Understanding the connection between rectified flows and optimal transport.
method Investigates invariance properties, explicit constructions, and analysis of rectified flows in various settings.
result Rectified flows, when gradient constrained, do not generally solve optimal transport problems.

Consider a nontrivial solution to a semilinear elliptic system of first order with smooth coefficients defined over an nn-dimensional manifold. Assume the operator has the strong unique continuation property. We show that the zero set of the solution is contained in a countable union of smooth (n2)(n-2)-dimensional subm…

1998-05-13abs ↗pdf ↗

We introduce a notion of rectifiability modeled on Carnot groups. Precisely, we say that a subset E of a Carnot group M and N is a subgroup of M, we say E is N-rectifiable if it is the Lipschitz image of a positive measure subset of N. First, we discuss the implications of N-rectifiability, where N is a Carnot group (n…

2000-04-11abs ↗pdf ↗

This paper studies rectifiability in Carnot groups and proves geometric area formulas.

problem The study of rectifiability in Carnot groups and related geometric properties.
method Analysis of rectifiable measures in Carnot groups, geometric area formulas, and rectifiability of geodesic spheres.
result Geometric area formula for the centered Hausdorff measure restricted to intrinsically differentiable graphs in Carnot groups.

New framework explains deep neural networks using variational spline theory.

problem Understanding functions learned by deep neural networks.
method Developed a variational framework and function space.
result Deep ReLU networks are solutions to regularized data fitting problems over the proposed function space.

New elastic energy for irregular curves defined through polygonal approximations.

problem Defining elastic energy for irregular curves in any space dimension.
method Relaxation process with pp-rotation of inscribed polygonals, focusing on geometric curvature distribution.
result Energy finite if and only if curve's arc-length parameterization has second order summability.

New rectifiability criteria for finite-perimeter sets in Carnot groups.

problem Rectifiability of finite-perimeter sets in Carnot groups.
method Introducing a new notion of rectifiability based on cone properties and studying semigroups generated by horizontal half-spaces.
result Finite-perimeter subsets in Carnot groups can be covered by countably many subsets with cone properties, leading to countable rectifiability with respect to intrinsic Lipschitz graphs.

Rectifies flat singular points of area-minimizing currents with singularity degree > 1.

problem Rectifying flat singular points of area-minimizing currents with singularity degree > 1.
method Subdividing singular points based on singularity degree and proving rectifiability of points with singularity degree > 1.
result The set of points with singularity degree > 1 is (m-2)-rectifiable.

We can compare the expressiveness of neural networks that use rectified linear units (ReLUs) by the number of linear regions, which reflect the number of pieces of the piecewise linear functions modeled by such networks. However, enumerating these regions is prohibitive and the known analytical bounds are identical for…

2018-10-08abs ↗pdf ↗

The paper proves strong uniqueness and rectifiability of generalized cylindrical singularities in Ricci flow.

problem Proving strong uniqueness and rectifiability of generalized cylindrical singularities in Ricci flow.
method Establishing a Lojasiewicz inequality for the pointed W\mathcal{W}-entropy in Ricci flow under the assumption of geometry near the base point being close to a generalized cylinder.
result Proves strong uniqueness of generalized cylindrical tangent flows and shows that the subset of points with rectifiable Sqck(N)\mathcal{S}^k_{\mathrm{qc}}(N) is horizontally parabolic.

The goal of this paper is to describe all local diffeomorphisms mapping a family of circles, in an open subset of $\r^3$, into straight lines. This paper contains two main results. The first is a complete description of the rectifiable collection of circles in $\r^3$ passing through one point. It turns out that to be r…

2003-01-20abs ↗pdf ↗

We show that metrics that maximize the k-th Steklov eigenvalue on surfaces with boundary arise from free boundary minimal surfaces in the unit ball. We prove several properties of the volumes of these minimal submanifolds. For free boundary minimal submanifolds in the ball we show that the boundary volume is reduced up…

2013-04-03abs ↗pdf ↗

A space curve in a Euclidean 3-space E3\mathbb E^3 is called a rectifying curve if its position vector field always lies in its rectifying plane. This notion of rectifying curves was introduced by the author in [Amer. Math. Monthly {\bf 110} (2003), no. 2, 147-152]. In this present article, we introduce and study the n…

2016-07-28abs ↗pdf ↗

A neural network with a single hidden layer can't represent certain multivariable functions.

problem Representing certain multivariable functions with a neural network having only one hidden layer.
method Developed a continuum version of a one-hidden-layer neural network with ReLU activation, and proved constraints on its parameters and second derivative.
result Existence of a smooth binary function that cannot be precisely represented by any such neural network.

New methods for solving hydrodynamic-type equations using quasi-rectifiable Lie algebras.

problem Solving systems of hydrodynamic-type equations.
method Introducing and analyzing quasi-rectifiable Lie algebras and vector fields.
result New methods for solving hydrodynamic-type equations.

The paper generalizes rectifying and normal curves in Lorentzian n-space.

problem Characterizing and classifying gg-rectifying and gg-normal curves in Lorentzian n-space.
method Introducing a gg-position vector field and defining gg-rectifying and gg-normal curves based on this field.
result Comprehensive characterization and classification of gg-rectifying and gg-normal curves.

In this paper we investigate the performance of different types of rectified activation functions in convolutional neural network: standard rectified linear unit (ReLU), leaky rectified linear unit (Leaky ReLU), parametric rectified linear unit (PReLU) and a new randomized leaky rectified linear units (RReLU). We evalu…

2015-05-05abs ↗pdf ↗

Neural networks can approximate rectifiable measures with small error.

problem Approximating complex rectifiable measures using neural networks.
method Using ReLU neural networks to approximate (countably) m-rectifiable measures as push-forwards of the Lebesgue measure.
result The approximation error in terms of Wasserstein distance can be made arbitrarily small.

We show that C^1 hypersurfaces in the Heisenberg group are countably N-rectifiable. As a corollary, this shows that all C^1_H graphs over the xy-plane are countable N-rectifiable, showing the equivalence of this notion of rectifiability with that of Franchi, Serra Cassano and Serapioni for such surfaces.

2004-07-13abs ↗pdf ↗

The paper characterizes special curves and generalizes rectifying-type curves in n-dimensional space.

problem Characterizing and generalizing special curves in higher dimensions.
method Characterization through Rotation minimizing frame (RMF) and generalization of rectifying-type curves.
result Rectifying-type curves are generalized in n-dimensional space.

Paper explores how Rectified Flow adapts to low-dimensional data.

problem Improving sampling efficiency in low-dimensional data.
method Investigates Rectified Flow's adaptation to low-dimensional support and introduces a stochastic version.
result Shows improved sampling efficiency with O(k/ε)O(k/\varepsilon) complexity.

In this paper, we introduce transformations of deep rectifier networks, enabling the conversion of deep rectifier networks into shallow rectifier networks. We subsequently prove that any rectifier net of any depth can be represented by a maximum of a number of functions that can be realized by a shallow network with a …

2017-03-30abs ↗pdf ↗

The paper characterizes rectifying curves on smooth surfaces using isometries and Darboux frames.

problem Characterizing rectifying curves on smooth surfaces under isometries.
method Using Darboux frames and isometries to investigate rectifying curves.
result Find deviations of rectifying curves under isometries and analyze their properties.

In this paper, we introduce a new class of curves αcalled a f-rectifying curves, which its f-position vector defined by α_{f}(s)=\int f(s)T(s)ds always lie in the rectifying plane of α, where f is an integrable function and T is the speed curve of α. In particular case, when the function f=0 or constant, the class of f…

2018-10-21abs ↗pdf ↗