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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.

168,742 papers · 148 categories

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1122 · Feb 201519922001200920172026
26 results for Hölder cocyle

Adversarial online nonparametric regression achieves optimal rates with locally adaptive learning.

problem Adversarial online nonparametric regression with general convex losses.
method Parameter-free learning algorithm leveraging chaining trees to compete against H{ö}lder functions, dynamically tracking and adapting to local smoothness variations.
result First computationally efficient algorithm with locally adaptive optimal rates for online regression in an adversarial setting.

We consider families of Dirac operators on the unit interval which depend on parameters via boundary conditions. We study the associated eta forms and Maslov cocyles. With this simple example we show how previous results of Lesch/Woiciechowski and the first author on the eta invariant of cylinders generalize to the fam…

1997-01-13abs ↗pdf ↗

The paper studies Hamiltonian flows for pseudo-Anosov mapping classes on surfaces.

problem Understanding the dynamics of pseudo-Anosov mapping classes on Teichmüller spaces.
method Explicit formulae for Hamiltonian flows generated by invariant functions.
result Hamiltonian flows coincide with the action of pseudo-Anosov homeomorphisms at time one.

The paper defines higher invariants for groups of polynomial growth and proves their convergence.

problem Defining and proving convergence of higher invariants for groups of polynomial growth.
method Using delocalized cyclic cocycles and a determinant map construction.
result A well-defined pairing between delocalized cyclic cocyles and K-theory classes of C*-algebraic secondary higher invariants.

Combinatorial aspects of the Torelli-Johnson-Morita theory of surface automorphisms are extended to certain subgroups of the mapping class groups. These subgroups are defined relative to a specified homomorphism from the fundamental group of the surface onto an arbitrary group KK. For KK abelian, there is a combinato…

2012-01-18abs ↗pdf ↗

In the context of stochastic continuum-armed bandits, we present an algorithm that adapts to the unknown smoothness of the objective function. We exhibit and compute a polynomial cost of adaptation to the H{ö}lder regularity for regret minimization. To do this, we first reconsider the recent lower bound of Locatelli an…

2019-05-24abs ↗pdf ↗

Given a biquandle (X,S)(X, S), a function ττ with certain compatibility and a pair of {\em non commutative cocyles} f,h:X×XGf,h:X \times X\to G with values in a non necessarily commutative group GG, we give an invariant for singular knots / links. Given (X,S,τ)(X,S,τ), we also define a universal group Uncfh(X)U_{nc}^{fh}(X) and universa…

2019-10-09abs ↗pdf ↗

We study finite energy classes of quasiplurisubharmonic (qpsh) functions in the setting of toric compact K{ä}hler manifolds. We characterize toric qpsh functions and give necessary and sufficient conditions for them to have finite (weighted) energy, both in terms of the associated convex function in R n , and through t…

2018-04-10abs ↗pdf ↗

Let SS be a closed oriented surface of genus at least 22, and denote by T(S)\mathcal{T}(S) its Teichm{ü}ller space. For any isotopy class of closed curves γγ, we compute the first three derivatives of the length function _γ:T(S)R_+\ell\_γ:\mathcal{T}(S)\rightarrow\mathbf{R}\_+ in the shearing coordinates associated to a maxim…

2015-06-22abs ↗pdf ↗

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 ↗

Validates economic scenarios using statistical tests on stochastic processes.

problem Ensuring the accuracy of real-world economic scenario models.
method Applies Chevyrev and Oberhauser's (2022) signature and maximum mean distance test to various stochastic processes.
result Demonstrates the test's effectiveness across different path properties relevant to financial modeling.

We find a local solution to the Ricci flow equation under a negative lower bound for many known curvature conditions. The flow exists for a uniform amount of time, during which the curvature stays bounded below by a controllable negative number. The curvature conditions we consider include 2-non-negative and weakly $\t…

2018-04-22abs ↗pdf ↗

Study shows zero-shot super-resolution in neural operators is impossible in many cases.

problem Understanding the theoretical limits of zero-shot super-resolution in neural operators.
method Systematic theoretical study including information-theoretic and generalization bounds analysis.
result Zero-shot super-resolution is information-theoretically impossible in many settings.

Efficient algorithms for contextual bandits with smooth regret in continuous action spaces.

problem Efficient learning in large or continuous action spaces.
method Smooth regret notion and efficient algorithms for general function approximation.
result Statistically and computationally efficient algorithms for contextual bandits with smooth regret.

This reports on the fundamental objects revealed by Ross Street, which he called `orientals'. Street's work was in part inspired by Robert's attempts to use N-category ideas to construct nets of C*-algebras in Minkowski space for applications to relativistic quantum field theory: Roberts' additional challenge was that …

2010-08-10abs ↗pdf ↗

General lower bounds on neural network approximation in L^p norm.

problem Fundamental limits of neural network expressivity.
method General lower bound proof on approximation in L^p norm, applied to feed-forward neural networks.
result Neural networks can't approximate certain functions as well as previously thought.

This paper selects features in deep neural networks with theoretical guarantees.

problem Feature selection in deep neural networks with unknown nonlinear functions.
method Reformulate neural networks as index models, estimate feature sets using Stein's formula, and apply screening-and-selection mechanism.
result Consistent feature selection with theoretical guarantees, even in high-dimensional settings.

New algorithms for interactive learning match minimax bounds efficiently.

problem Interactive learning in the realizable setting with computational efficiency.
method General framework, computationally efficient algorithms, Monte Carlo hit-and-run sampling.
result Sample complexities quantifiable in terms of combinatorial quantities, computationally efficient.

Introduces a space of almost complex structures for complex Lie group bundles.

problem Integrability of almost complex structures on complex Lie group bundles.
method Introduces a space of bundle almost complex structures and studies their properties.
result Locally pseudo-holomorphic sections exist if and only if the obstruction form is zero.