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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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25.0%50.0%75.0%100.0% · Sep 199219922001200920172026
48 results for non-linear groups

Classifies non-linear Fredholm maps linking to stable homotopy groups of spheres.

problem Classifying non-linear proper Fredholm maps between Hilbert spaces.
method Using stable homotopy groups of spheres to classify maps up to proper homotopy.
result Determines the non-trivial kernel of the map from stable homotopy groups to non-linear proper Fredholm maps.

The paper generalizes equivariant neural networks on homogeneous spaces to the non-linear setting.

problem Equivariant neural networks on homogeneous spaces.
method Deriving generalized steerability constraints for non-linear equivariant layers.
result The universality of the derived construction for non-linear equivariant layers.

Generalizing the canonical symplectization of contact manifolds, we construct an infinite dimensional non-linear Stiefel manifold of weighted embeddings into a contact manifold. This space carries a symplectic structure such that the contact group and the group of reparametrizations act in a Hamiltonian fashion with eq…

2019-09-24abs ↗pdf ↗

We present a geometric construction of central extensions of covering groups of the group of volume preserving diffeomorphisms, integrating central extensions of the Lie algebra of divergence free vector fields defined by Lichnerowicz cocycles. Certain covering spaces of non-linear Grassmannians can be realized as preq…

2010-07-31abs ↗pdf ↗

SAFLe solves federated learning's trade-off between non-linearity and scalability.

problem Federated Learning's high communication overhead and performance collapse on non-IID data.
method SAFLe introduces a structured head of bucketed features and sparse, grouped embeddings, mathematically equivalent to a high-dimensional linear regression.
result SAFLe achieves a new state-of-the-art in analytic FL, outperforming linear AFL and multi-round DeepAFL.

For a given manifold MM we consider the non-linear Grassmann manifold Grn(M)Gr_n(M) of nn-dimensional submanifolds in MM. A closed (n+2)(n+2)-form on MM gives rise to a closed 2-form on Grn(M)Gr_n(M). If the original form was integral, the 2-form will be the curvature of a principal S1S^1-bundle over Grn(M)Gr_n(M). Using this $S^…

2003-05-06abs ↗pdf ↗

Improved disability insurance model with collective health claims.

problem Enhance disability insurance model with collective health claims.
method Expand classic semi-Markov model with collective health claims, solve many-body problem using mean-field approach.
result Mean-field approach simplifies complex model into a transparent pricing method.

Let G be a rank two finite group, and let $\cH$ denote the family of rank one p-subgroups of G, at all primes where G has p-rank two. We show that a rank two finite group G which satisfies certain group-theoretic conditions admits a finite G-CW-complex X with isotropy in $\cH$, whose fixed sets are homotopy spheres. Ou…

2013-02-03abs ↗pdf ↗

We discuss from a geometric point of view the connection between the renormalization group flow for non--linear sigma models and the Ricci flow. This offers new perspectives in providing a geometrical landscape for 2D quantum field theories. In particular we argue that the structure of Ricci flow singularities suggests…

2010-01-20abs ↗pdf ↗

In this paper, we investigate the non-linear Black--Scholes equation: ut+ax2uxx+bx3uxx2+c(xuxu)=0,a,b>0, c0.u_t+ax^2u_{xx}+bx^3u_{xx}^2+c(xu_x-u)=0,\quad a,b>0,\ c\geq0. and show that the one can be reduced to the equation ut+(uxx+ux)2=0u_t+(u_{xx}+u_x)^2=0 by an appropriate point transformation of variables. For the resulting equation, we study the group-theore…

2015-11-30abs ↗pdf ↗

New proof of generalized Chow-Rashevskii theorem for non-linear systems.

problem Generalized Chow-Rashevskii Theorem for non-linear systems.
method Independent proof structure allowing generalizations to orbits of compositions of flows.
result Proof structure applicable to applications in Control Theory and controllability criteria.

Estimates signals from a continuous dictionary with sparse mixtures using optimization.

problem Estimating signals from a continuous dictionary with unknown mixtures and noise.
method Formulates a regularized optimization problem with data fidelity and (1,Lp)(\ell_1,L^p)-penalty.
result High probability bounds on prediction error for the Group-Nonlinear-Lasso solution.

We give dimension-free regularity conditions for a class of possibly degenerate sub-elliptic equations in the Heisenberg group exhibiting super-quadratic growth in the horizontal gradient; this solves an issue raised by Manfredi & Mingione (Math. Ann. 2007) where only dimension dependent bounds for the growth exponent …

2007-08-27abs ↗pdf ↗

For a closed symplectic manifold (M,ω)(M,ω) with compatible Riemannian metric gg we study the Sobolev H1H^1 geometry of the group of all HsH^s diffeomorphisms on MM which preserve the symplectic structure. We show that, for sufficiently large ss, the H1H^1 metric admits globally defined geodesics and the corresponding …

2017-10-08abs ↗pdf ↗

In this paper we examine the Riemannian geometry of the group of contactomorphisms of a compact contact manifold. We compute the sectional curvature of Dθ(M)\mathcal{D}_θ(M) in the sections containing the Reeb field and show that it is non-negative. We also solve explicitly the Jacobi equation along the geodesic correspon…

2015-01-09abs ↗pdf ↗

SL(N,C) is the phase space of the Poisson SU(N). We calculate explicitly the symplectic structure of SL(N,C), define an analogue of the Hamiltonian of the free motion on SU(N) and solve the corresponding equations of motion. Velocity is related to the momentum by a non-linear Legendre transformation.

1996-12-04abs ↗pdf ↗

Study the geometry of hydrodynamics equations using diffeomorphism groups.

problem Investigate the Euler equations and surface quasi-geostrophic equation family.
method Realize equations as geodesic equations on diffeomorphism groups and analyze Riemannian exponential maps.
result Show precise conditions for non-linear Fredholm maps of index 0.

Unified method for CNNs to approximate equivariant maps across various groups.

problem Limited universal approximation theorems for CNNs with specific groups and settings.
method Unified approach to derive universal approximation theorems for equivariant maps by CNNs in diverse settings.
result Ability to handle non-linear equivariant maps between infinite-dimensional spaces for non-compact groups.

Geometry arising from two diffusion operators (smooth semi-elliptic, second order differential operators) on different spaces but intertwined by a smooth map is described. Particular cases arise from Riemannian submersions when the operators are Laplace-Beltrami operators, from equivariant operators on the total space …

2008-10-13abs ↗pdf ↗

Recent developments in the understanding of N=2N=2 supersymmetric Yang-Mills theory in four dimensions suggest a new point of view about Donaldson theory of four manifolds: instead of defining four-manifold invariants by counting SU(2)SU(2) instantons, one can define equivalent four-manifold invariants by counting solution…

1994-11-15abs ↗pdf ↗

In this note, we study non-linear gauge theories for principal bundles, where the structure group is replaced by a Lie groupoid. We follow the approach of Moerdijk-Mrcun and establish its relation with the existing physics literature. In particular, we derive a new formula for the gauge transformation which closely res…

2008-07-21abs ↗pdf ↗

The geometric non-linear Schrodinger equation (GNLS) on the complex Grassmannian manifold M is the Hamiltonian equation for the energy functional on C(R,M) with respect to the symplectic form induced from the Kahler form on M. It has a Lax pair that is gauge equivalent to the Lax pair of the matrix non-linear Schroding…

1999-01-21abs ↗pdf ↗

Researchers can retrieve Yang-Mills-Higgs fields from Minkowski space measurements.

problem Retrieving Yang-Mills-Higgs fields from active local measurements in Minkowski space.
method Exploiting non-linear wave interactions and Lie algebra structure.
result Yang-Mills-Higgs fields can be retrieved from source-to-solution data.

The paper studies the holonomy of spherically symmetric Finsler metrics.

problem Investigating the holonomy group of spherically symmetric projective Finsler metrics of constant curvature.
method Analyzing the holonomy group for nn-dimensional projective Finsler metrics of constant curvature, focusing on the spherically symmetric case.
result For a simply connected manifold, the holonomy group is isomorphic to Diffo(Sn1)Diff_o({\mathbb S^{n-1}}), the connected component of the identity of the group of smooth diffeomorphisms on the (n1)(n-1)-dimensional sphere.

We develop the theory of equivariant harmonic self-maps of compact cohomogeneity one manifolds and construct new harmonic self-maps of the compact Lie groups SO(4L+2), L >= 1, with degree -3, of SO(8), SO(14) and SO(26) with degree -5 each, of SO(10) with degree -7, and of SO(14) with degree -11 by exhibiting linear so…

2016-08-30abs ↗pdf ↗

The L2L^2-metric or Fubini-Study metric on the non-linear Grassmannian of all submanifolds of type MM in a Riemannian manifold (N,g)(N,g) induces geodesic distance 0. We discuss another metric which involves the mean curvature and shows that its geodesic distance is a good topological metric. The vanishing phenomenon for…

2004-09-17abs ↗pdf ↗

This study evaluates handwriting features to diagnose Parkinson's disease.

problem Diagnosing Parkinson's disease through handwriting analysis.
method Kinematic, geometrical, and non-linear features were evaluated using K-nearest neighbors, support vector machines, and random forest classifiers.
result Up to 93.1% accuracy in classifying Parkinson's disease and healthy subjects.

Two Fisher information matrix estimators are analyzed for neural networks, focusing on their variances and trade-offs.

problem Estimating the Fisher information matrix in neural networks due to its high computational cost.
method Examined two popular diagonal Fisher information matrix estimators and their variances in neural networks for regression and classification.
result The variances of the estimators depend on the non-linearity with respect to different parameter groups and should not be neglected.

In genomic analysis, biomarker discovery, image recognition, and other systems involving machine learning, input variables can often be organized into different groups by their source or semantic category. Eliminating some groups of variables can expedite the process of data acquisition and avoid over-fitting. Research…

2019-11-29abs ↗pdf ↗

Paper uses non-linear dimension reduction for better economic forecasting.

problem Analyzing economic effects of shocks in large datasets.
method Non-linear dimension reduction in factor-augmented vector autoregressions.
result Non-linear dimension reduction techniques improve forecasting, especially in volatile data.

TaCo prevents non-linear classifiers from detecting sensitive attributes.

problem Ensuring fairness in NLP models by preventing sensitive attribute detection.
method Targeted Concept Erasure (TaCo) removes sensitive information from final latent representations, even against non-linear classifiers.
result TaCo outperforms state-of-the-art methods in reducing sensitive attribute prediction accuracy while preserving overall task performance.

We present a PDE-based framework that generalizes Group equivariant Convolutional Neural Networks (G-CNNs). In this framework, a network layer is seen as a set of PDE-solvers where geometrically meaningful PDE-coefficients become the layer's trainable weights. Formulating our PDEs on homogeneous spaces allows these net…

2020-01-24abs ↗pdf ↗