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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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48 results for finite dimensional bases

We propose a method for pricing American options whose pay-off depends on the moving average of the underlying asset price. The method uses a finite dimensional approximation of the infinite-dimensional dynamics of the moving average process based on a truncated Laguerre series expansion. The resulting problem is a fin…

2010-11-16abs ↗pdf ↗

The paper studies multi-curve interest rate models and their consistency and finite-dimensional realizations.

problem Consistency and existence of finite-dimensional realizations for multi-curve interest rate models.
method Geometric approach, characterizing consistency and existence of finite-dimensional realizations for multi-curve models.
result Characterization of consistency and existence of finite-dimensional realizations for multi-curve models.

Simplified Ricci curvature for spherical fluid dynamics models.

problem Studying stability in incompressible fluid dynamics on a sphere.
method Definition and calculation of Ricci curvature for two-dimensional hydrodynamics using finite-dimensional Zeitlin models.
result Strong numerical evidence suggests convergence of finite-dimensional approximations to infinite-dimensional limit, indicating average instability for high-frequency modes.

High-dimensional models trained on smooth manifolds achieve optimal rates in Wasserstein metrics.

problem Training score-based generative models on complex, low-dimensional manifolds.
method Proves optimal rates for SGMs on smooth manifolds, separating into noise regimes and using ReLU nearest-projection coordinates.
result Optimal intrinsic Wasserstein rates are achieved, with polynomial ambient dependence for families with controlled geometry and density.

Infinite-dimensional SBDMs improve image generation across multiple resolutions.

problem Efficient image generation at high resolutions and across different levels.
method Developed SBDMs in infinite-dimensional setting, using trace class operators and operator networks.
result Improved efficiency and generalization across resolution levels.

We present a finite-dimensional version of the quantum model for the stock market proposed in [C. Zhang and L. Huang, A quantum model for the stock market, Physica A 389(2010) 5769]. Our approach is an attempt to make this model consistent with the discrete nature of the stock price and is based on the mathematical for…

2012-04-17abs ↗pdf ↗

Paper provides finite-sample guarantees for Wasserstein DRO without dimensionality curse.

problem Tackles empirical success of Wasserstein DRO in operations and ML with performance guarantees.
method Develops non-asymptotic framework for analyzing out-of-sample performance and generalization bound.
result First finite-sample guarantee for generic Wasserstein DRO problems without curse of dimensionality.

This is an expository paper about Seiberg-Witten Floer stable homotopy types. We outline their construction, which is based on the Conley index and finite dimensional approximation. We then describe several applications, including the disproof of the high-dimensional triangulation conjecture.

2013-08-29abs ↗pdf ↗

Study transverse measures on infinite type hyperbolic surfaces.

problem Characterize the cone of transverse measures on infinite type hyperbolic surfaces.
method Use inverse limits and geodesic laminations to describe and construct cones of transverse measures.
result Explicit descriptions and bases of cones of transverse measures exist for many laminations.

Develops a finite construction for self-duality and related moduli spaces over Riemann surfaces.

problem Constructing moduli spaces over Riemann surfaces.
method Finite-dimensional construction using holomorphic symplectic reduction.
result Moduli spaces over Riemann surfaces as stratified holomorphic symplectic spaces.

We study finite-time collapsing limits of the continuity method. When the continuity method starting from a rational initial Kähler metric on a projective manifold encounters a finite-time volume collapsing, this projective manifold admits a Fano fibration over a lower dimensional base. In this case, we prove the conti…

2016-12-05abs ↗pdf ↗

A machine learning model manages portfolio risk in high dimensions.

problem Managing risk in high-dimensional financial portfolios.
method A supervised learning approach using replicating martingales and polynomial/neural network bases.
result The model outperforms naive Monte Carlo and least-squares Monte Carlo methods.

Let M be a compact Riemannian manifold without boundary and let H be a self-adjoint generalized Laplace operator acting on sections in a bundle over M. We give a path integral formula for the solution to the corresponding heat equation. This is based on approximating path space by finite dimensional spaces of geodesic …

2007-03-09abs ↗pdf ↗

The paper extends graph-based semi-supervised learning to infinite-dimensional Wasserstein space.

problem Graph-based semi-supervised learning in high-dimensional data.
method Laplace Learning in the Wasserstein space, proving variational convergence and characterizing the Laplace-Beltrami operator.
result Consistent classification performance in high-dimensional settings.

In a 1967 paper, Banchoff stated that a certain type of polyhedral curvature, that applies to all finite polyhedra, was zero at all vertices of an odd-dimensional polyhedral manifold; one then obtains an elementary proof that odd-dimensional manifolds have zero Euler characteristic. In a previous paper, the author defi…

2003-10-30abs ↗pdf ↗

Based on projective representations of smooth Deligne cohomology groups, we introduce an analogue of the space of conformal blocks to compact oriented (4k+2)-dimensional Riemannian manifolds with boundary. For the standard (4k+2)-dimensional disk, we compute the space concretely to prove that its dimension is finite.

2007-05-25abs ↗pdf ↗

We develop a new theoretical framework to analyze the generalization error of deep learning, and derive a new fast learning rate for two representative algorithms: empirical risk minimization and Bayesian deep learning. The series of theoretical analyses of deep learning has revealed its high expressive power and unive…

2017-05-29abs ↗pdf ↗

Finite-dimensional spaces of biharmonic functions on manifolds are explored.

problem Characterizing biharmonic functions on open manifolds with nonnegative Ricci curvature.
method Analyzing bounded and polynomial growth biharmonic functions, deriving Weyl bounds, and studying fourth-order operators.
result Finite-dimensional spaces of biharmonic functions with polynomial growth are established.

The popular cubic smoothing spline estimate of a regression function arises as the minimizer of the penalized sum of squares j(Yjμ(tj))2+λab[μ"(t)]2dt\sum_j(Y_j - μ(t_j))^2 + λ\int_a^b [μ"(t)]^2 dt, where the data are tj,Yjt_j,Y_j, j=1,...,nj=1,..., n. The minimization is taken over an infinite-dimensional function space, the space of all functions wi…

2011-11-08abs ↗pdf ↗

A lattice based method will be presented for numerical investigations of Ricci flow. The method will be applied to the particular case of 2-dimensional axially symmetric initial data on manifolds with S^2 topology. Results will be presented that show that the method works well and agrees with results obtained using con…

2015-12-10abs ↗pdf ↗

Exact inference method for Wasserstein distance with finite-sample coverage.

problem Asymptotic approximation methods for Wasserstein distance lack finite-sample validity.
method Selective Inference inspired approach for exact inference.
result Valid confidence interval for Wasserstein distance with finite-sample coverage.

Cannon, Floyd, and Parry have studied subdivisions of the 2-sphere extensively, especially those corresponding to 3-manifolds, in an attempt to prove Cannon's conjecture. There has been a recent interest in generalizing some of their tools, such as extremal length, to higher dimensions. We define finite subdivision rul…

2011-10-14abs ↗pdf ↗

Proposes a new gauge theory for fuzzy geometries using finite-dimensional algebras.

problem Modeling fuzzy geometries in noncommutative geometry.
method Introduces a Yang-Mills-Higgs matrix model based on gauge matrix spectral triples.
result States Yang-Mills-Higgs theory as an explicit random multimatrix model.

Solves classical problem with Kähler-Einstein metrics in complex projective spaces.

problem Classical problem of non-isometric bidimensional Kähler-Einstein submanifolds.
method Listed complete non-isometric bidimensional rotation invariant Kähler-Einstein submanifolds.
result Solves the classical problem in the specified case.

A new ML algorithm solves complex economic control problems.

problem Solving high-dimensional, finite-horizon stochastic control problems in economics.
method Deep neural network representation of optimal policy functions with three key features.
result Efficiently solves various economic control problems including recursive utility and growth models.

We show in this note that the Sobolev Discrepancy introduced in Mroueh et al in the context of generative adversarial networks, is actually the weighted negative Sobolev norm .H˙1(νq)||.||_{\dot{H}^{-1}(ν_q)}, that is known to linearize the Wasserstein W2W_2 distance and plays a fundamental role in the dynamic formulation of…

2018-05-16abs ↗pdf ↗

M. Hennings and G. Kuperberg defined quantum invariants Z_{Henn} and Z_{Kup} of closed oriented 3-manifolds based on certain Hopf algebras, respectively. We prove that |Z_{Kup}|=|Z_{Henn}|^2 for lens spaces when both invariants are based on factorizable finite dimensional ribbon Hopf algebras.

2011-06-16abs ↗pdf ↗