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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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98196293391 · Jun 202019922001200920172026
48 results for Lipschitz Class

Defines a new modulus for Lipschitz surfaces and proves a homological duality theorem.

problem Lipschitz homology classes and their moduli.
method Defining a new modulus dModp\operatorname{dMod}_p and proving a homological duality theorem.
result Every relative Lipschitz kk-homology class has a unique dual class satisfying a specific modulus product equality.

Extends Lipschitz functions while preserving local constants.

problem Extending Lipschitz functions on metric spaces while maintaining local constants.
method Extends Lipschitz functions on metric spaces while locally preserving the asymptotic Lipschitz constant.
result Sobolev spaces on metric measure spaces are invariant under isomorphism of mm-structures.

We focus our attention on the notion of intrinsic Lipschitz graphs, inside a special class of metric spaces i.e. the Carnot groups. More precisely, we provide a characterization of locally intrinsic Lipschitz functions in Carnot groups of step 2 in terms of their intrinsic distributional gradients.

2019-03-06abs ↗pdf ↗

We characterize locally Lipschitz mappings and existence of Lipschitz extensions through a first order nonlinear system of PDEs. We extend this study to graded group-valued Lipschitz mappings defined on compact Riemannian manifolds. Through a simple application, we emphasize the connection between these PDEs and the Ru…

2007-11-30abs ↗pdf ↗

Characterizes quasi-isometric embeddings in coarsely Lipschitz category.

problem Understanding quasi-isometric embeddings in geometric terms.
method Formalizes quasi-isometric embeddings as regular monomorphisms in coarsely Lipschitz category.
result Quasi-isometric embeddings are equivalently characterised as effective, strong, or extremal monomorphisms.

The local Lipschitz constant of a neural network is a useful metric with applications in robustness, generalization, and fairness evaluation. We provide novel analytic results relating the local Lipschitz constant of nonsmooth vector-valued functions to a maximization over the norm of the generalized Jacobian. We prese…

2020-03-02abs ↗pdf ↗

We consider Aubry-Mather theory for a subclass of class A spacetimes, i.e. compact vicious spacetimes with globally hyperbolic Abelian cover. In this subclass, called class A_1, we obtain improved results on timelike maximizers and Lipschitz continuity of the time separation of the Abelian cover on the i.g. optimal sub…

2011-04-19abs ↗pdf ↗

New scalable Lipschitz bounds improve neural network robustness analysis.

problem Computing tight Lipschitz bounds for deep neural networks is challenging and computationally expensive.
method Derived new closed-form Lipschitz bounds using more general feasible points of LipSDP, avoiding SDP solvers.
result Improved scalability and precision of Lipschitz estimation for large neural networks.

We define self-adjoint extensions of the Hodge Laplacian on Lipschitz domains in Riemannian manifolds, corresponding to either the absolute or the relative boundary condition, and examine regularity properties of these operators' domains and form domains. We obtain results valid for general Lipschitz domains, and stron…

2004-08-31abs ↗pdf ↗

Maps and measures on surfaces link best Lipschitz and least gradient functions.

problem Analyzing maps between surfaces and their geometric properties.
method Duality between best Lipschitz and least gradient maps, geodesic laminations, and transverse measures.
result The infinity harmonic map defines a geodesic lamination and the least gradient map defines a transverse measure.

In this paper we prove that every definable set has a definable triangulation which is locally Lipschitz and weakly bi-Lipschitz on the natural simplicial stratification of the simplicial complex. We also distinguish a class T of regularity conditions and give a universal construction of a definable triangulation with …

2009-04-08abs ↗pdf ↗

Proves new concentration inequalities for sub-gaussian and sub-exponential variables.

problem Understanding functions of independent random variables better.
method Sub-gaussian and sub-exponential conditions, Rademacher complexities, Lipschitz function classes.
result Extension of Rademacher complexities to unbounded sub-exponential distributions.

We study Anosov representations whose limit set has intermediate regularity, namely is a Lipschitz submanifold of a flag manifold. We introduce an explicit linear functional, the unstable Jacobian, whose orbit growth rate is integral on this class of representations. We prove that many interesting higher rank represent…

2019-10-15abs ↗pdf ↗

Sharp Lipschitz bounds for flow-matching and diffusion models with optimal sampling rates.

problem Establishing optimal Lipschitz regularity for flow-matching and diffusion models.
method Sharp Lipschitz regularity theory for flow-matching vector fields and diffusion-model scores.
result Achieves optimal sampling rate of d/N\sqrt{d}/N for Euler-type samplers in dimension dd.

GD-trained shallow ReLU nets learn Lipschitz functions with noise.

problem Learning Lipschitz functions with additive noise in overparameterized neural networks.
method Gradient Descent (GD) with early stopping, focusing on the Neural Tangent Kernel (NTK).
result Early-stopped GD achieves minimax optimal rates for learning Lipschitz functions.

The paper studies Lipschitz bounds for integral kernels under differentiability assumptions.

problem Understanding the Lipschitz continuity of feature maps associated with integral kernels.
method Analyzes differentiability assumptions to derive explicit formulas for Lipschitz constants and conditions for non-Lipschitz continuity.
result Explicit formulas and conditions for Lipschitz continuity of feature maps associated with various kernels.

New parameterization of neural networks with Lipschitz bounds for robustness.

problem Developing robust neural networks with Lipschitz bounds.
method Introducing a new parameterization that admits a Lipschitz bound during training without requiring projections or barrier functions.
result The new parameterization improves robustness to adversarial attacks in image classification.

Given a Hopf fibration of a round sphere by parallel great subspheres, we prove that the projection map to the base space is, up to isometries of domain and range, the unique Lipschitz constant minimizer in its homotopy class. Similarly, given a Hopf fibration of a round sphere by parallel great circles, we view a unit…

2010-09-28abs ↗pdf ↗

The study establishes equivalence of conditions on metric manifolds with finite volume.

problem Characterizing metric spaces with a metric fundamental class.
method Analyzing three conditions on metric manifolds with finite volume.
result Conditions (1), (2), and (3) are equivalent for metric manifolds with finite Nagata dimension.

We investigate the challenge of multi-output learning, where the goal is to learn a vector-valued function based on a supervised data set. This includes a range of important problems in Machine Learning including multi-target regression, multi-class classification and multi-label classification. We begin our analysis b…

2020-02-22abs ↗pdf ↗

In [9] Kaimanovich introduced the concept of augmented tree on the symbolic space of a self-similar set. It is hyperbolic in the sense of Gromov, and it was shown in [13] that under the open set condition, a self-similar set can be identified with the hyperbolic boundary of the tree. In the paper, we investigate in det…

2012-05-16abs ↗pdf ↗

Uniform heat kernel bounds lead to synthetic Ricci curvature conditions for Lipschitz manifolds.

problem Establishing synthetic Ricci curvature conditions for Lipschitz manifolds.
method Uniform heat kernel bounds and synthetic Ricci curvature conditions.
result Uniform heat kernel bounds lead to synthetic Ricci curvature conditions for Lipschitz manifolds.

We find maximal representatives within equivalence classes of metric spheres. For Ahlfors regular spheres these are uniquely characterized by satisfying the seemingly unrelated notions of Sobolev-to-Lipschitz property, or volume rigidity. We also apply our construction to solutions of the Plateau problem in metric spac…

2019-09-23abs ↗pdf ↗

The problem of adversarial examples has highlighted the need for a theory of regularisation that is general enough to apply to exotic function classes, such as universal approximators. In response, we give a very general equality result regarding the relationship between distributional robustness and regularisation, as…

2020-02-11abs ↗pdf ↗

Lipschitz mappings found between Riemann surfaces with specific properties.

problem Finding globally Lipschitz mappings between doubly connected Riemann surfaces.
method Using a result from Iwaniec, Kovalev, and Onninen, the minimizer of the energy functional is shown to be locally Lipschitz and globally Lipschitz.
result The minimizer of the energy functional is a globally Lipschitz mapping.

Efficient binary sampling method for global optimization of univariate functions with low regret.

problem Global optimization of univariate loss functions.
method Binary sampling approach to circumvent hard-to-determine query points in traditional methods.
result At most Llog(3T)L\log (3T) and 2.25H2.25H regret for LL-Lipschitz continuous and HH-Lipschitz smooth functions respectively.