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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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51102152203 · May 202619922001200920172026
48 results for divergence theorems

The divergence theorem in its usual form applies only to suitably smooth vector fields. For vector fields which are merely piecewise smooth, as is natural at a boundary between regions with different physical properties, one must patch together the divergence theorem applied separately in each region. We give an elegan…

1994-04-02abs ↗pdf ↗

Bregman divergences play a central role in the design and analysis of a range of machine learning algorithms. This paper explores the use of Bregman divergences to establish reductions between such algorithms and their analyses. We present a new scaled isodistortion theorem involving Bregman divergences (scaled Bregman…

2016-07-01abs ↗pdf ↗

The transformation formula of the Berezin integral holds, in the non-compact case, only up to boundary integrals, which have recently been quantified by Alldridge-Hilgert-Palzer. We establish divergence theorems in semi-Riemannian supergeometry by means of the flow of vector fields and these boundary integrals, and sho…

2013-09-05abs ↗pdf ↗

We study the divergence theorem on pseudo-Finsler spaces and obtain a completely Finslerian version for spaces having a vanishing mean Cartan torsion. This result helps to clarify the problem of energy-momentum conservation in Finsler gravity theories.

2015-08-25abs ↗pdf ↗

The study tightens bounds on binomial probabilities and minimums using KL-divergence.

problem Tightening bounds on binomial probabilities and minimums of i.i.d. Binomials.
method Applied Sanov's theorem to derive upper and lower bounds on binomial tail probabilities and minimums, expressed in terms of KL-divergence.
result High probability upper and lower bounds on the minimum of i.i.d. Binomial random variables, finite sample, asymptotically tight.

The paper studies a generalized Pythagorean theorem on dually flat spaces via toric geometry.

problem Understanding the geometry of dually flat spaces and their toric Kähler manifolds.
method Introducing a dually flat structure and Bregman divergence on the boundary of toric Kähler manifolds.
result A continuity and generalized Pythagorean theorem for the divergence on the boundary.

The paper studies λλ-submanifolds in Gauss spaces and proves theorems for complete proper ones.

problem Understanding λλ-submanifolds in Gauss spaces and their properties.
method Using divergence type theorems and Simons' identities, the authors prove theorems for complete proper λλ-submanifolds.
result Proves halfspace and gap theorems for complete proper λλ-submanifolds, generalizing previous results.

New theorem links symmetries to first integrals in plasma physics.

problem Understanding the relationship between symmetries and first integrals in divergence-free fields.
method Developed a Noether-type Theorem reformulation for three-dimensional divergence-free vector fields.
result Converse of the Noether-type Theorem holds on the toroidal region, proving the existence of flux coordinates.

The paper is devoted to differential geometry of singular distributions (i.e., of varying dimension) on a Riemannian manifold. Such distributions are defined as images of the tangent bundle under smooth endomorphisms. We prove the novel divergence theorem with the divergence type operator and deduce the Codazzi equatio…

2019-08-20abs ↗pdf ↗

Extends Masur's divergence theorem to complex tori and Kummer surfaces.

problem Establishing uniquely ergodic horizontal foliations for geodesic flows on moduli spaces.
method Defined and calculated horizontal foliations and geodesic flows on moduli spaces of Kähler metrics.
result Proved that horizontal foliations are uniquely ergodic if geodesic flows are recurrent.

New dual formulation reduces generalization error for ERM-fDR.

problem Generalization error in constrained optimization problems.
method Introduces a dual formulation of ERM-fDR using Legendre-Fenchel transform and implicit function theorem.
result Explicit characterizations of generalization error for algorithms under mild conditions.

We lay the foundations for a theory of divergence-measure fields in noncommutative stratified nilpotent Lie groups. Such vector fields form a new family of function spaces, which generalize in a sense the BVBV fields. They provide the most general setting to establish Gauss-Green formulas for vector fields of low regul…

2018-06-08abs ↗pdf ↗

We provide geometric conditions on a pair of hyperplanes of a CAT(0) cube complex that imply divergence bounds for the cube complex. As an application, we classify all right-angled Coxeter groups with quadratic divergence and show right-angled Coxeter groups cannot exhibit a divergence function between quadratic and cu…

2016-11-14abs ↗pdf ↗

New divergence identity for scalar curvature helps prove rigidity of tensors.

problem Proving rigidity of Codazzi tensors under curvature and invariant conditions.
method Derived a divergence identity for a vector field and applied it to tensor rigidity.
result New proof of Tang-Yan theorem on constant eigenvalues for tensors.

New Wasserstein divergence improves generative model robustness and structure preservation.

problem Improving generative model robustness and structure preservation.
method Introduces a novel Wasserstein-1 path-space divergence and a WUP theorem.
result Derives robustness and generalization bounds for flow-based models.

In the field of statistics, many kind of divergence functions have been studied as an amount which measures the discrepancy between two probability distributions. In the differential geometrical approach in statistics (information geometry), dually flat spaces play a key role. In a dually flat space, there exist dual a…

2018-08-16abs ↗pdf ↗

Optimized α\alpha-posteriors reduce KL divergence from true posterior in parametric misspecification.

problem Reduction of KL divergence from true posterior in parametric model misspecification.
method Derivation of Bernstein-von Mises theorem and optimization of α\alpha-posteriors.
result Optimized α\alpha-posteriors minimize KL divergence from true posterior, especially in severe misspecification.

Neural networks estimate statistical divergences with performance guarantees.

problem Estimating statistical divergences with theoretical performance guarantees.
method Parametrizing empirical variational form by a neural network and optimizing over parameter space.
result Established non-asymptotic absolute error bounds for neural estimators of four f\mathsf{f}-divergences.

In this paper we prove that Dirac operators on non-compact complete orbifolds which are sufficiently regular at infinity, admit a unique extension. Additonally, we prove a generalized orbifold Stokes'/Divergence theorem.

2006-01-18abs ↗pdf ↗

This paper is devoted to the study of convergence of sequences of solutions to the constant mean curvature H equation. The convergence domain is defined. The main Theorem characterizes the complement of this convergence domain: it shows that circle arcs of curvature 2H compose this complement. We then give results whic…

2005-09-21abs ↗pdf ↗

Dual optimization connects ERM-fDR to normalization function.

problem Empirical risk minimization with f-divergence regularization.
method Dual formulation, Legendre-Fenchel transform, implicit function theorem, nonlinear ODE.
result Computational method to calculate normalization function efficiently.

Unified analysis of KL divergence using shifted composition for sampling.

problem Sampling from target distributions with KL divergence guarantees.
method Shifted composition rule applied to KL divergence, combining local error analysis and Girsanov's theorem.
result Unified KL guarantees for strongly log-concave, weakly log-concave, and log-Sobolev distributions.

Positive definite matrices abound in a dazzling variety of applications. This ubiquity can be in part attributed to their rich geometric structure: positive definite matrices form a self-dual convex cone whose strict interior is a Riemannian manifold. The manifold view is endowed with a "natural" distance function whil…

2011-10-08abs ↗pdf ↗

Proposes a new learning method for RBMs that combines strengths of forward and reverse KLD.

problem Underfitting and mode-collapse issues in RBM learning.
method Ratio divergence learning using target energy.
result Significantly outperforms other learning methods in energy function fitting, mode-covering, and stability.

This paper provides performance guarantees for neural estimation of statistical distances.

problem Developing performance guarantees for neural estimation of statistical distances.
method Non-asymptotic error bounds using function approximation theorems and empirical process theory.
result Established a fundamental tradeoff between approximation and estimation errors in neural estimation of statistical distances.

Global solutions found for a wave-Klein-Gordon system with strong couplings in divergence form.

problem Global well-posedness of a wave-Klein-Gordon system with strong couplings in divergence form.
method Constructed an auxiliary system with shifted primitives to handle the strong couplings.
result Established global well-posedness theorem for the wave-Klein-Gordon system.

Threshold found for hyperbolicity in random Coxeter groups.

problem Determining the hyperbolicity threshold in random Coxeter groups.
method Analyzing random right-angled Coxeter groups via Erdős-Rényi graphs and combinatorial properties.
result Threshold p=1/np=1/\sqrt{n} for relative hyperbolicity in random Coxeter groups.

A function is exponentially concave if its exponential is concave. We consider exponentially concave functions on the unit simplex. In a previous paper we showed that gradient maps of exponentially concave functions provide solutions to a Monge-Kantorovich optimal transport problem and give a better gradient approximat…

2016-05-19abs ↗pdf ↗

We prove a Filling Theorem for the Heisenberg Groups H2n+1H^{2n+1}: For a given kk-cycle aa we construct a (k+1)(k+1)-chain bb (the filling) with boundary b=a\partial b=a and controlled volume. For this filling bb we prove a uniform bound on the distance of points in bb to its boundary aa. Using this we compute the high…

2014-10-14abs ↗pdf ↗

Information theoretic measures (e.g. the Kullback Liebler divergence and Shannon mutual information) have been used for exploring possibly nonlinear multivariate dependencies in high dimension. If these dependencies are assumed to follow a Markov factor graph model, this exploration process is called structure discover…

2016-09-13abs ↗pdf ↗

We prove a theorem formulated by V. I. Arnold concerning a relation between the asymptotic linking number and the Hopf invariant of divergence-free vector fields. Using a modified definition for the system of short paths, we prove their existence in the general case.

2000-11-21abs ↗pdf ↗

We give background which shows the connection between the mean value theorem and the obstacle problem, and then we prove that a set is a mean value set for an elliptic operator of the form Lu:=i(aij(x)ju(x))Lu := \partial_i (a^{ij}(x) \partial_j u(x)) if and only if it arises as the noncontact set of an obstacle problem involving the …

2019-07-29abs ↗pdf ↗

For a complete Riemannian manifold MM with an (1,1)-elliptic Codazzi self-adjoint tensor field AA on it, we use the divergence type operator LA(u):=div(Au){L_A}(u): = div(A\nabla u) and an extension of the Ricci tensor to extend some major comparison theorems in Riemannian geometry. In fact we extend theorems like mean curvature…

2018-11-27abs ↗pdf ↗

We compute all 2-covariant tensors naturally constructed from a semiriemannian metric which are divergence-free and have weight greater than -2. As a consequence, it follows a characterization of the Einstein tensor as the only, up to a constant factor, 2-covariant tensor naturally constructed from a semiriemannian met…

2007-09-12abs ↗pdf ↗

Let (X, g) be an arbitrary pseudo-riemannian manifold. A celebrated result by Lovelock gives an explicit description of all second-order natural (0,2)-tensors on X, that satisfy the conditions of being symmetric and divergence-free. Apart from the dual metric, the Einstein tensor of g is the simplest example. In this p…

2010-05-13abs ↗pdf ↗