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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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16.7%33.3%50.0%66.7% · Jan 199319922001200920172026
48 results for Fast Gauss transform

Paper presents a fast algorithm for pricing Bermudan swaptions under the two-factor Hull-White model.

problem Evaluating Bermudan swaption prices under the two-factor Hull-White model with high computational efficiency.
method Discretization of expected value calculation, Gaussian kernel sums, fast Gauss transform, grid rotation for stability.
result Significant reduction in computation time and improved stability for correlation close to -1.

Kernel density estimation (KDE) is a popular statistical technique for estimating the underlying density distribution with minimal assumptions. Although they can be shown to achieve asymptotic estimation optimality for any input distribution, cross-validating for an optimal parameter requires significant computation do…

2011-02-14abs ↗pdf ↗

Approximate Newton methods are a standard optimization tool which aim to maintain the benefits of Newton's method, such as a fast rate of convergence, whilst alleviating its drawbacks, such as computationally expensive calculation or estimation of the inverse Hessian. In this work we investigate approximate Newton meth…

2015-07-29abs ↗pdf ↗

Study spherical Fourier transform on hypergeometric type harmonic manifolds.

problem Spherical Fourier transform on harmonic Hadamard manifolds.
method Representation of spherical functions by Gauss hypergeometric functions.
result Inversion formula, convolution rule, and Plancherel theorem are derived.

Study finite curvature solutions on surfaces with nonnegative Gauss curvature.

problem Finite total curvature solutions of Liouville equation on surfaces with nonnegative Gauss curvature.
method Analyzes asymptotic behavior of solutions on complete surfaces.
result Two extremal cases identified: Euclidean plane or flat cylinder, with specific decay conditions.

Study D4D_4^--front singularities, compute invariants, and derive a Gauss-Bonnet theorem.

problem Characterize and analyze D4D_4^--front singularities in 3D space.
method Develop coordinate transformations and isometries, compute differential invariants.
result Derive a Gauss-Bonnet type theorem for D4D_4^--fronts.

New curvature measures for 4D manifolds with corners defined and related to Gauss-Bonnet.

problem Defining curvature measures for 4D manifolds with corners.
method Defined two new extrinsic curvature quantities, one conformal invariant, and a new conformally invariant operator.
result Gauss-Bonnet theorem reformulated in terms of new curvature measures.

The Gauss-Newton method is analyzed for neural networks using Riemannian optimization techniques.

problem Training neural networks with smooth activations and convergence rates.
method Riemannian optimization perspective, analyzing the Gauss-Newton method in both underparameterized and overparameterized regimes.
result Geometric convergence rates independent of conditioning and eigenvalues, demonstrating accelerated convergence.

We describe the gauge-theoretic approach to transformations in integrable geometry through discussion of two classical examples: surfaces of constant negative Gauss curvature and isothermic surfaces. These are purely expository notes written to accompany some lectures I gave in Fukuoka in May 2015.

2015-11-13abs ↗pdf ↗

We introduce a topological approach to words. Words are approximated by Gauss words and then studied up to natural modifications inspired by homotopy transformations of curves on the plane.

2005-03-29abs ↗pdf ↗

Efficient algorithm finds fast Transformer models.

problem Slow inference time of Transformer models.
method Decompose Transformer architecture into components, use sampling-based one-shot search.
result Achieved 10% to 30% speedup on pre-trained BERT and 70% on top of a previous state-of-the-art model.

In this paper, we study strong r-helix hypersurfaces and the special curves on these surfaces. Moreover, we investigated the relations between strong r-helix hypersurfaces and the Gauss transformations of these surfaces in Euclidean n-space.

2012-03-07abs ↗pdf ↗

A new algorithm computes Fourier coefficients for a specified range efficiently.

problem Inefficiency in FFT due to fixed output size for all applications.
method Fast Partial Fourier Transform (PFT) that allows specifying the range of Fourier coefficients to compute.
result PFT achieves significant speedup over state-of-the-art FFT algorithms for small output sizes.

Analytical pricing formulas and Greeks are obtained for European and American basket put options using Mellin transforms. We assume assets are driven by geometric Brownian motion which exhibit correlation and pay a continuous dividend rate. A novel approach to numerical Mellin inversion is achieved via the fast Fourier…

2014-03-15abs ↗pdf ↗

Proves long-term smoothness of curved surfaces evolving under specific curvature rules.

problem Long-term regularity of curved surfaces evolving under pp-Gauss curvature flow.
method Transformed the curvature flow into a Monge-Ampère equation and studied its asymptotic cone.
result Proved regularity of the interface in all dimensions for $p> rac1n$.

Study curvature of piecewise metrics using moving frames.

problem Deriving a curvature measure for piecewise-smooth Riemannian metrics.
method Used moving frame techniques to derive curvature, showing it satisfies Cartan structure equations and gauge transformation law.
result Equivalence of the derived curvature to existing densitized distributional curvature.

MultiRocket boosts TSC speed and accuracy with pooling and transformations.

problem Efficient time series classification with high accuracy.
method Multiple pooling operators and transformations applied to raw and differenced series.
result MultiRocket outperforms MiniRocket and is competitive with state-of-the-art methods in terms of accuracy and speed.

In this paper, we propose several dictionary learning algorithms for sparse representations that also impose specific structures on the learned dictionaries such that they are numerically efficient to use: reduced number of addition/multiplications and even avoiding multiplications altogether. We base our work on facto…

2018-12-09abs ↗pdf ↗

The 1-d Schrodinger flow on 2-sphere, the Gauss-Codazzi equation for flat Lagrangian submanifolds in C^n, and the space-time monopole equation are all examples of geometric soliton equations. The linear systems with a spectral parameter (Lax pair) associated to these equations satisfy the reality condition associated t…

2006-11-03abs ↗pdf ↗

Survey on recent developments in isometric immersions using PDE techniques.

problem Analyzing isometric immersions with low Sobolev regularity.
method Compensated compactness and Coulomb-Uhlenbeck gauges.
result Weak continuity and stability of Gauss-Codazzi-Ricci equations.

In this paper we form relations for the determination of the elements of the Eötvös matrix of the Earth's normal gravity field. In addition a relation between the Gauss curvature of the normal equipotential surface and the Gauss curvature of the actual equipotential surface both passing through the point P is presented…

2011-07-11abs ↗pdf ↗

Efficiently approximates eigenspaces for symmetric and general matrices.

problem Fast computation of eigenspaces for large matrices.
method Factor eigenspaces into fundamental components using transformations, solve minimization problems, and iteratively update.
result Improved computational efficiency for eigenspace approximation.

Bayesian deep learning avoids underfitting by projecting onto null space of generalized Gauss-Newton matrix.

problem Bayesian deep learning often underfits, leading to less accurate predictions than point estimates.
method Proposes a matrix-free algorithm to project onto the null space of the generalized Gauss-Newton matrix, ensuring Bayesian predictions do not underfit.
result The method scales to large models, including vision transformers with 28 million parameters, and avoids underfitting.

Enhances Fourier estimator performance for asynchronous event-data.

problem Improving correlation and covariance estimation on event-data.
method Implement and test NUFFT methods with different averaging kernels.
result Demonstrates improved performance and relationship between averaging scales.

In this paper, we derive the price of a European call option of an asset following a normal process assuming stochastic volatility. The volatility is assumed to follow the Cox Ingersoll Ross (CIR) process. We then use the fast Fourier transform (FFT) to evaluate the option price given we know the characteristic functio…

2019-09-17abs ↗pdf ↗

A Laguerre geometric local characterization is given of L-minimal surfaces and Laguerre deformations (T-transforms) of L-minimal isothermic surfaces in terms of the holomorphicity of a quartic and a quadratic differential. This is used to prove that, via their Laguerre Gauss maps, the T-transforms of L-minimal isotherm…

2014-01-08abs ↗pdf ↗

New algorithms improve RPCA for large matrices with upper rank bounds.

problem Efficiently decompose large matrices into low-rank and sparse parts.
method Combine regularization and matrix multiplication approaches with upper rank bounds.
result Proposed algorithms are faster and more robust than existing methods.

We provide fast algorithms for overconstrained p\ell_p regression and related problems: for an n×dn\times d input matrix AA and vector bRnb\in\mathbb{R}^n, in O(ndlogn)O(nd\log n) time we reduce the problem minxRdAxbp\min_{x\in\mathbb{R}^d} \|Ax-b\|_p to the same problem with input matrix A~\tilde A of dimension s×ds \times d and corr…

2012-07-19abs ↗pdf ↗