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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.

168,695 papers · 148 categories

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3978117156 · Jun 202019922001200920172026
48 results for Dudley's Integral

This paper proves a generalization bound for complex-valued neural networks scaling with spectral complexity.

problem Ensuring the performance of complex-valued neural networks on unseen data.
method Theoretical derivation using Maurey Sparsification Lemma and Dudley Entropy Integral, empirical validation on various datasets.
result The spectral complexity of weight matrices is a significant factor in the generalization ability of complex-valued neural networks.

The paper develops generalization bounds for deep compound Gaussian neural networks.

problem Developing theoretical guarantees for the performance of deep neural networks.
method Novel generalization error bounds using a compound Gaussian prior and Dudley's integral.
result Theoretical bounds show generalization error scales O(nln(n))\mathcal{O}(n\sqrt{\ln(n)}) in signal dimension and O((NetworkSize)3/2)\mathcal{O}((Network Size)^{3/2}) in network size.

Improved neural network reconstruction from sparse measurements with theoretical guarantees.

problem Improving neural network performance in sparse signal reconstruction from few measurements.
method Combining iterative reconstruction algorithms with neural networks, analyzing generalization properties, and deriving a generalization bound.
result Theoretical guarantees for neural network reconstruction from compressive linear measurements, with generalization error scaling logarithmically in the number of layers and linearly in the number of measurements.

Extends Optimal Transport to multiple agents, aiming for equitable and optimal distribution.

problem Sharing costs or goods equitably among multiple agents with different preferences.
method Minimizes the maximum transportation cost or maximizes the minimum utility.
result Provides a new algorithm faster than standard linear programming.

Study shows depth improves generalization in deep learning models.

problem Understanding why and when depth improves generalization in deep learning.
method Implementation-agnostic state-transition model to analyze depth and generalization.
result Identifies geometric and semigroup mechanisms that keep entropy contribution saturated or polynomial, clarifying depth's statistical advantage.

We consider the problem of online nonparametric regression with arbitrary deterministic sequences. Using ideas from the chaining technique, we design an algorithm that achieves a Dudley-type regret bound similar to the one obtained in a non-constructive fashion by Rakhlin and Sridharan (2014). Our regret bound is expre…

2015-02-26abs ↗pdf ↗

The paper analyzes how machine learning models perform under covariate shift, especially when the feature shift in xx is larger than that in yy.

problem Performance of machine learning models under covariate shift with heterogeneous feature changes.
method Empirical risk minimization (ERM) over functions f+gf+g, fit on a training distribution, evaluated on a test distribution with covariate shift.
result ERM is more resilient to heterogeneous covariate shifts when the class FF is simpler than GG.

We study the problem of reconstructing an unknown matrix M of rank r and dimension d using O(rd poly log d) Pauli measurements. This has applications in quantum state tomography, and is a non-commutative analogue of a well-known problem in compressed sensing: recovering a sparse vector from a few of its Fourier coeffic…

2011-03-14abs ↗pdf ↗

Bounding the generalization error of learning algorithms has a long history, which yet falls short in explaining various generalization successes including those of deep learning. Two important difficulties are (i) exploiting the dependencies between the hypotheses, (ii) exploiting the dependence between the algorithm'…

2018-06-11abs ↗pdf ↗

MSRL learns a representation maximizing mutual info with response variables.

problem Learning sufficient representations for complex, multi-dimensional data.
method Variational mutual information, deep neural networks, generalized Dudley's inequality.
result MSRL achieves consistent and accurate representation learning.

Unified framework for robust clustering under various dissimilarity measures.

problem Improving center-based clustering methods to handle outliers and non-Euclidean data.
method Median-of-Means (MoM) estimation framework with uniform concentration bounds.
result Strong consistency and error rate of O(n1/2)O(n^{-1/2}) under mild conditions.

The study examines stability of Hamiltonian Poisson integrators on both integrable and non-integrable systems.

problem Investigating stability properties of Hamiltonian Poisson integrators.
method Examples of Lotka-Volterra dynamics and numerical investigations of a non-integrable system are used.
result The existence of a modified Hamiltonian is crucial for the stability of Hamiltonian Poisson integrators.

The paper defines and analyzes set-valued stochastic integrals for Lévy processes.

problem Defining and analyzing set-valued stochastic integrals for Lévy processes.
method Extending classical definitions to convoluted integrals with square-integrable kernels, and proving properties of set-valued convoluted stochastic integrals.
result Set-valued convoluted stochastic integrals can be explosive and take extended vector values.

We discuss a recurrent geometrical method, due to Élie Cartan and von Weber ([1],[11]) enabling us to determine, step by step, the maximal integral manifolds of a not necessarily integrable nor regular Pfaffian system. The dimensions of such integral manifolds can, of course, vary from point to point but more so can va…

2016-08-09abs ↗pdf ↗

We define a non-absolutely convergent integration on integral currents of dimension 1 in Euclidean space. This integral is closely related to the Henstock-Kurzweil and Pfeffer Integrals. Using it, we prove a generalized Fundamental Theorem of Calculus on these currents. A detailed presentation of Henstock-Kurzweil Inte…

2019-05-08abs ↗pdf ↗

Study integrable geodesic flows on 2-surfaces with high-degree polynomial first integrals.

problem Integrable geodesic flows on 2-surfaces with high-degree polynomial first integrals.
method Semi-Hamiltonian systems of PDEs and generalized hodograph method.
result Construction of many local explicit and implicit integrable examples with polynomial first integrals of degrees 3, 4, 5.

The article constructs stochastic integration in Riemannian manifolds.

problem No specific problem stated; focuses on the construction of stochastic integration.
method Functional-analytic approach to stochastic integration in Riemannian manifolds.
result There are infinitely many stochastic integrals, and they are related by a simple formula.

Constructs Lie groupoid integrating elliptic tangent bundles and Poisson structures.

problem Existence and integration of elliptic tangent bundles and Poisson structures.
method Explicit construction of Lie groupoids and local models for symplectic integration.
result Necessary and sufficient topological condition for integration of elliptic tangent bundles.

Investigates integrable systems with linear periodic integral for e(3) Lie algebra.

problem Analyzes singularities and topological properties of integrable systems.
method Examines singularities of Liouville foliation, bifurcation diagram, transformations of Liouville tori, and isoenergy surfaces.
result Discovers topological properties of integrable systems with linear periodic integral.

We use neural networks as control variates with geometric integration techniques.

problem Analytic integration of neural network approximations for variance reduction.
method Integration domain subdivision using computational geometry for MLPs with continuous piecewise linear activation functions.
result Neural networks can be used as control variates with geometric integration methods.

Integral foliated simplicial volume is a version of simplicial volume combining the rigidity of integral coefficients with the flexibility of measure spaces. In this article, using the language of measure equivalence of groups we prove a proportionality principle for integral foliated simplicial volume for aspherical m…

2014-03-18abs ↗pdf ↗

This paper is an exposition of heuristics related to Witten's functional integral, relating it to Vassiliev invariants and to the Kontsevich integrals that can be used to produce Vassiliev invariants of knots and links.In particular, we give a simplified version of the appearance of the Kontsevich integrals in the pert…

1998-11-23abs ↗pdf ↗

This paper provides an existence-and-uniqueness theorem characterizing the stochastic integral with respect to a Wiener process. The integral is represented as a mapping from the space of measurable and adapted pathwise locally integrable processes to the space of continuous adapted processes. It is characterized in te…

2018-12-23abs ↗pdf ↗

We construct an infinite-dimensional symplectic 2-groupoid as the integration of an exact Courant algebroid. We show that every integrable Dirac structure integrates to a "Lagrangian" sub-2-groupoid of this symplectic 2-groupoid. As a corollary, we recover a result of Bursztyn-Crainic-Weinstein-Zhu that every integrabl…

2013-10-24abs ↗pdf ↗

The linking integral is an invariant of the link-type of two manifolds immersed in a Euclidean space. It is shown that the ordinary Gauss integral in three dimensions may be simplified to a winding number integral in two dimensions. This result is then generalized to show that in certain circumstances the linking integ…

2009-07-20abs ↗pdf ↗

New integrable deformations for topological hierarchies from Frobenius manifolds.

problem Integrable deformations of topological hierarchies from Frobenius manifolds.
method Construction of integrable deformations with polynomial tau-structures.
result Conjecture of universal object for Riemann--Hopf hierarchy.

Sharp lower bound found for integral varifolds' mean curvature.

problem Finding a sharp lower bound for the mean curvature integral of integral varifolds.
method Developed a new approach using integral varifolds and mean curvature.
result A sharp lower bound on the mean curvature integral with critical power for integral varifolds.

Proves a theorem for normal distributions on manifolds with boundary.

problem Normal distributions on manifolds with boundary require a new approach to integration.
method Introduces neat integral manifolds with boundary and conditions for integrability.
result Conditions for integrability expressed in terms of adapted collars and integrability on interior and boundary.

The paper proves conditions for Darboux integrability in diagonal hydrodynamic systems.

problem Conditions for Darboux integrability in diagonal hydrodynamic systems.
method Proof of conditions using Laplace transformation sequences and geometric interpretations.
result Diagonal systems of hydrodynamic type are Darboux integrable if and only if the corresponding systems for commuting flows are Darboux integrable.

A new method integrates forms on Riemann surfaces, leading to modular forms.

problem Integrating differential forms with poles on Riemann surfaces.
method Simple procedure to integrate differential forms with arbitrary holomorphic poles, establishing an analytic theory for integrals over configuration spaces.
result Regularized graph integrals on elliptic curves are almost-holomorphic modular forms.

Researchers prove integrability of magnetic systems on spheres up to dimension 6.

problem Integrability of magnetic systems on spheres restricted to their surface.
method Proved complete integrability for n ≤ 6, noncommutative integrability for n ≥ 7, conjectured integrability for all n.
result Complete integrability of magnetic flows on spheres for n ≤ 6, noncommutative integrability for n ≥ 7.

A new geometric definition of integration for differential forms.

problem Standard integration definitions are coordinate-dependent and not suitable for certain contexts.
method Uses triangulations and cochains on the pair groupoid to define integration.
result Natural definition in Lie algebroids, stochastic integration, and quantum field theory.

We prove that a holomorphic Lie algebroid is integrable if, and only if, its underlying real Lie algebroid is integrable. Thus the integrability criteria of Crainic-Fernandes do also apply in the holomorphic context without any modification. As a consequence we give another proof of the following theorem: a holomorphic…

2008-03-13abs ↗pdf ↗