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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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255075100 · Jun 202019922001200920172026
48 results for Hilbert polynomials

We prove that the degree of the Hilbert polynomial of the HOMFLYPT homology of a closed braid BB is l1l-1, where ll is the number of components of BB. This controls the growth of the HOMFLYPT homology with respect to its polynomial grading. The Hilbert polynomial also reveals a link polynomial hidden in the HOMFLYPT…

2016-04-18abs ↗pdf ↗

The paper calculates the Hilbert polynomials for configuration spaces over graphs with a short circumference.

problem Calculating the Betti numbers of configuration spaces over graphs with a short circumference.
method Using a combinatorial approach based on the canonical 1-bridge decomposition of the graph.
result An expression for the Hilbert polynomial of a graph in terms of its canonical 1-bridge decomposition.

We prove that the metric balls of a Hilbert geometry admit a volume growth at least polynomial of degree their dimension. We also characterise the convex polytopes as those having exactly polynomial volume growth of degree their dimension.

2012-07-04abs ↗pdf ↗

We solve for functions from their truncated Hilbert transforms using Chebyshev series.

problem Finding functions from their truncated Hilbert transforms.
method Express functions in Chebyshev series and numerically estimate coefficients.
result Numerical methods work well for extrapolating functions from truncated Hilbert transforms.

Hilbert's 17th problem asks that whether every nonnegative polynomial can be a sum of squares of rational functions. It has been answered affirmatively by Artin. However, the question as to whether a given nonnegative polynomial is a sum of squares of polynomials is still a central question in real algebraic geometry. …

2018-11-14abs ↗pdf ↗

Study on gradient descent in Hilbert spaces with Markov chains, focusing on mixing coefficients.

problem Analyzing convergence of gradient descent in Hilbert spaces with stationary Markov chains.
method Examined strictly stationary Markov chains with φφ- and ββ-mixing coefficients, derived probabilistic upper bounds.
result Probabilistic upper bounds on convergence behavior of gradient descent algorithm based on mixing coefficients.

We represent algebraic curves via commuting matrix polynomials. This allows us to show that the Hilbert scheme of cohomologically stable twisted rational curves of degree dd in P3\P1{\Bbb P}^3\backslash {\Bbb P}^1 is isomorphic to a complexified hyperkähler quotient of an open subset of a vector space by a non-reductive …

2019-03-05abs ↗pdf ↗

Seidel and Smith have constructed an invariant of links as the Floer cohomology for two Lagrangians inside a complex affine variety Y. This variety is the intersection of a semisimple orbit with a transverse slice at a nilpotent in the Lie algebra sl2m.sl_{2m}. We exhibit bijections between a set of generators for the Sei…

2004-10-31abs ↗pdf ↗

A method for interpreting SVMs using polynomial kernels, revealing model complexity.

problem Interpreting SVMs built with truncated orthogonal polynomial kernels.
method Orthogonal Representation Contribution Analysis (ORCA) with normalized Orthogonal Kernel Contribution (OKC) indices.
result The method reveals structural aspects of model complexity not captured by predictive accuracy.

Study analyzes learnability of RKHS under L∞ norm for kernel methods.

problem Understand performance of kernel methods and random feature models.
method Relate L∞ learnability to kernel spectrum decay and establish sample complexity bounds.
result Conditions for efficient L∞ learning of RKHS identified.

A representation of the Jacobi algebra h1su(1,1)\mathfrak{h}_1\rtimes \mathfrak{su}(1,1) by first order differential operators with polynomial coefficients on the manifold C×D1\mathbb{C}\times \mathcal{D}_1 is presented. The Hilbert space of holomorphic functions on which the holomorphic first order differential operators with …

2004-08-17abs ↗pdf ↗

Given a planar curve singularity, we prove a conjecture of Oblomkov-Shende, relating the geometry of its Hilbert scheme of points to the HOMFLY polynomial of the associated algebraic link. More generally, we prove an extension of this conjecture, due to Diaconescu-Hua-Soibelman, relating stable pair invariants on the c…

2012-10-23abs ↗pdf ↗

We develop the theory of resolvent degree, introduced by Brauer \cite{Br} in order to study the complexity of formulas for roots of polynomials and to give a precise formulation of Hilbert's 13th Problem. We extend the context of this theory to enumerative problems in algebraic geometry, and consider it as an intrinsic…

2018-03-11abs ↗pdf ↗

We emphasize some properties of coherent state groups, i.e. groups whose quotient with the stationary groups, are manifolds which admit a holomorphic embedding in a projective Hilbert space. We determine the differential action of the generators of the representation of coherent state groups on the symmetric Fock space…

2002-11-04abs ↗pdf ↗

This paper provides mathematical foundations for regression methods used in forward initial margin approximation.

problem Developing robust methods for approximating forward initial margin.
method Introduces mathematical rigor to show that regression methods are variations of approximating the conditional expectation function.
result Each regression method is a numerical estimation of the conditional expectation with a different functional form.

This paper formulates a generalization of our work on quantum knots to explain how to make quantum versions of algebraic, combinatorial and topological structures. We include a description of previous work on the construction of Hilbert spaces from the states of the bracket polynomial with applications to algorithms fo…

2011-05-01abs ↗pdf ↗

The paper extends invariant theory to non-compact and non-reductive actions, classifying four regimes.

problem Extending invariant theory to non-compact and non-reductive actions.
method Examined two specific settings: discrete subgroups of Lorentz group acting on Rn,1\mathbb{R}^{n,1} and cocompact actions on smooth manifolds.
result Classification of invariant-theoretic regimes into four categories, identifying boundaries of Hilbert--Weyl and Schwarz theorems.

The paper constructs instanton complexes on stratified pseudomanifolds.

problem Analyzing functions with non-isolated critical points on singular spaces.
method Constructing Witten instanton complexes and Hilbert complexes.
result Proves Morse inequalities for stratified pseudomanifolds.

We compute the Hilbert polynomial and the Poincare function counting the number of fixed jet-order differential invariants of conformal metric structures modulo local diffeomorphisms, and we describe the field of rational differential invariants separating generic orbits of the diffeomorphism pseudogroup action. This r…

2016-04-22abs ↗pdf ↗

We present a holomorphic representation of the Jacobi algebra hnsp(n,R)\mathfrak{h}_n\rtimes \mathfrak{sp}(n,\R) by first order differential operators with polynomial coefficients on the manifold Cn×Dn\mathbb{C}^n\times \mathcal{D}_n. We construct the Hilbert space of holomorphic functions on which these differential operators a…

2006-04-18abs ↗pdf ↗

Ridge regression performs optimally in noisy environments with heavy-tailed distributions.

problem Performance of ridge regression in noisy environments with heavy-tailed noise.
method Established excess risk bounds using integral operator framework and Fuk-Nagaev inequality.
result Ridge regression achieves optimal convergence rates under heavy-tailed noise, demonstrating robustness.

Develops analytic methods for Lefschetz and Morse theories on stratified pseudomanifolds.

problem Analytic framework for Lefschetz and Morse theories on stratified pseudomanifolds.
method Heat kernel and Witten deformation based techniques for global and local Lefschetz numbers and Morse polynomials.
result Formulas for Lefschetz numbers and Morse polynomials as supertraces over cohomology groups of Hilbert complexes.

We prove that the ring $\Aff{\R}{M}$ of all polynomials defined on a real algebraic variety MRnM\subset\R^n is dense in the Hilbert space $L^2(M,e^{-|x|^2}\deμ)$, where $\deμ$ denotes the volume form of MM and $\deν=e^{-|x|^2}\deμ$ the Gaussian measure on MM.

1998-04-24abs ↗pdf ↗

We study learning properties of accelerated gradient descent methods for linear least-squares in Hilbert spaces. We analyze the implicit regularization properties of Nesterov acceleration and a variant of heavy-ball in terms of corresponding learning error bounds. Our results show that acceleration can provides faster …

2019-05-30abs ↗pdf ↗

Stochastic gradient descent achieves polynomial convergence rates for noiseless linear models.

problem Convergence analysis of stochastic gradient descent in noiseless linear models.
method Fixed step-size stochastic gradient descent on least-square risk.
result Polynomial convergence rates depend on the regularities of the optimum and feature vectors.

We compute the Heegaard-Floer link homology of algebraic links in terms of the multivariate Hilbert function of the corresponding plane curve singularities. The main result of the paper identifies four homologies: (a) the Heegaard-Floer link homology of the local embedded link of the germ, (b) the lattice homology asso…

2013-01-31abs ↗pdf ↗

Paper develops an online learning algorithm for functional data models.

problem Recovering slope functions or predictors in functional data models.
method Online regularized learning algorithm in reproducing kernel Hilbert spaces with polynomially decaying step-size.
result Established fast convergence rates for estimation error without capacity assumption.

This paper is an introduction to Khovanov homology, starting with the Kauffman bracket state summation, emphasizing the Bar-Natan Canopoloy and tangle cobordism approach. The paper discusses a simplicial approach to Khovanov homology and a quantum model for it so that the graded Euler characteristic that produces the J…

2011-07-07abs ↗pdf ↗

We discuss relations between quantum BPS invariants defined in terms of a product decomposition of certain series, and difference equations (quantum A-polynomials) that annihilate such series. We construct combinatorial models whose structure is encoded in the form of such difference equations, and whose generating fun…

2016-08-23abs ↗pdf ↗

We compute the quotient of the self-duality equation for conformal metrics by the action of the diffeomorphism group. We also determine Hilbert polynomial, counting the number of independent scalar differential invariants depending on the jet-order, and the corresponding Poincaré function. We describe the field of rati…

2016-05-04abs ↗pdf ↗

In the framework of finite order variational sequences a new class of Lagrangians arises, namely, \emph{special} Lagrangians. These Lagrangians are the horizontalization of forms on a jet space of lower order. We describe their properties together with properties of related objects, such as Poincaré--Cartan and Euler--…

2001-11-09abs ↗pdf ↗

Paper proposes a method for early stopping in regression using reproducing kernels.

problem Early stopping for iterative learning algorithms in nonparametric regression.
method Data-driven rule based on minimum discrepancy principle, validated by fixed-point analysis of localized Rademacher complexities.
result The proposed rule is minimax-optimal and performs comparably to cross-validation.

New method finds global minima using function evaluations and kernel approximations.

problem Finding global minima of smooth functions with limited evaluations.
method Approximates the function using infinite sums of square smooth functions and solves the optimization problem with polynomial time complexity.
result Achieves optimal number of function evaluations with theoretical guarantees and nearly optimal convergence rate.

Generalizes randomized SVD for better matrix approximations using Gaussian vectors.

problem Computing accurate rank-k approximations of matrices with limited data.
method Extends randomized SVD to multivariate Gaussian vectors, incorporating prior knowledge and using Gaussian processes.
result Demonstrates improved accuracy in approximating matrices and Hilbert-Schmidt operators.

We show how spectral filters can improve the convergence of numerical schemes which use discrete Hilbert transforms based on a sinc function expansion, and thus ultimately on the fast Fourier transform. This is relevant, for example, for the computation of fluctuation identities, which give the distribution of the maxi…

2017-06-29abs ↗pdf ↗

The paper shows how neural networks can approximate PDEs with polynomial scaling in dimension.

problem Understanding the complexity of approximating PDE solutions with neural networks.
method Developed a proof technique to simulate gradient descent using neural networks.
result Neural network parameters scale polynomially with input dimension for approximating PDE solutions.

We introduce closed-form transition density expansions for multivariate affine jump-diffusion processes. The expansions rely on a general approximation theory which we develop in weighted Hilbert spaces for random variables which possess all polynomial moments. We establish parametric conditions which guarantee existen…

2011-04-28abs ↗pdf ↗