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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.

168,657 papers · 148 categories

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19375674 · May 202619922001200920172026
48 results for canonical neighbourhoods

We find canonical decompositions for finitely presented groups which specialize to the classical JSJ-decomposition when restricted to the fundamental groups of Haken manifolds. The decompositions that we obtain are invariant under automorphisms of the group. A crucial new ingredient is the concept of a regular neighbou…

2001-10-19abs ↗pdf ↗

Let G be a finitely presented group. Scott and Swarup have constructed a canonical splitting of G which encloses all almost invariant sets over virtually polycyclic subgroups of a given length. We give an alternative construction of this regular neighbourhood, by showing that it is the tree of cylinders of a JSJ splitt…

2008-11-14abs ↗pdf ↗

Smooth flows with surgery approximate weak mean curvature flows with spherical and neck-pinch singularities.

problem Approximating weak mean curvature flows with singularities using smooth flows.
method Combining Choi-Haslhofer-Hershkovits and Choi-Haslhofer-Hershkovits-White work on canonical neighbourhoods and barriers to flows with surgery.
result Smooth flows with surgery can approximate weak mean curvature flows with spherical and neck-pinch singularities.

We study the Hamiltonian vector field v=(f/w,f/z)v=(-\partial f/\partial w,\partial f/\partial z) on C2\mathbb C^2, where f=f(z,w)f=f(z,w) is a polynomial in two complex variables, which is non-degenerate with respect to its Newton's polygon. We introduce coordinates in four-dimensional neighbourhoods of the "points at infinity", in …

2011-07-11abs ↗pdf ↗

We describe a semi-local canonical form for Legendrian foliations on contact manifolds in the neighbourhood of a Legendrian submanifold. This result generalizes local results by Libermann and Pang on Legendrian foliations on contact manifolds, and is analogeous to a semi-local result by Weinstein in the symplectic case…

2014-11-16abs ↗pdf ↗

The paper classifies path structures on 3D Lie groups and reduces non-flat ones to Z/2Z-structures.

problem Classifying and reducing path structures on 3D Lie groups.
method Analyzes curvature and automorphism groups to reduce path structures to simpler forms.
result Automorphism groups of non-flat path structures are maximal dimension 3.

The paper proves symplectic neighbourhood theorems for stratified subspaces.

problem Finding symplectic neighbourhoods of stratified subspaces.
method Analogy with Weinstein's neighbourhood theorem, strong version of Moser's trick, and tubular neighbourhood theorem.
result Generalization of existing constructions for exotic Lagrangians.

We quantify conditions that ensure that a signed measure on a Riemannian manifold has a well defined centre of mass. We then use this result to quantify the extent of a neighbourhood on which the Riemannian barycentric coordinates of a set of n+1n+1 points on an nn-manifold provide a true coordinate chart, i.e., the ba…

2016-06-05abs ↗pdf ↗

We describe for any Riemannian manifold a certain infinitesimal neighbourhood of the diagonal. Semi-conformal maps are analyzed as those that preserve such neighbourhoods; harmonic maps are analyzed as those that preserve mirror image formation for pairs of points in such neighbourhoods.

2003-06-12abs ↗pdf ↗

In the context of synthetic differential geometry, we study the Laplace operator an a Riemannian manifold. The main new aspect is a neighbourhood of the diagonal, smaller than the second neighbourhood usually required as support for second order differential operators. The new neighbourhood has the property that a func…

2000-06-23abs ↗pdf ↗

A new ensemble method using random projections for kNN classification.

problem Improving kNN classification accuracy through ensemble methods.
method Random projection of bootstrap samples into lower dimensions, using extended neighbourhood rule for base learners.
result Enhanced classification accuracy compared to traditional kNN and other ensembles.

The Freund family of distributions becomes a Riemannian 4-manifold with Fisher information as metric; we derive the induced αα-geometry, i.e., the αα-curvature, αα-Ricci curvature with its eigenvales and eigenvectors, the αα-scalar curvature etc. We show that the Freund manifold has a positive constant 0-scalar cur…

2003-11-06abs ↗pdf ↗

In this paper, it is shown that a large set of connections on a suitable sub-bundle of the tangent bundle of a Finsler Manifold can be used to study all the properties of convex neighbourhoods with respect to the Finsler Metric, which are needed to see that any Complete Finsler Space is Geodesically Connected.

2010-06-04abs ↗pdf ↗

This paper is concerned with the location of nodal sets of eigenfunctions of the Dirichlet Laplacian in thin tubular neighbourhoods of hypersurfaces of the Euclidean space of arbitrary dimension. In the limit when the radius of the neighbourhood tends to zero, it is known that spectral properties of the Laplacian are a…

2014-06-16abs ↗pdf ↗

Topological manifolds can be embedded flatly in high-dimensional Euclidean space and are locally retracts.

problem Embedding and retraction of topological manifolds in Euclidean spaces.
method Locally flat embedding and retraction of manifolds in high-dimensional Euclidean space.
result Every topological n-manifold can be embedded locally flatly in R2n+1R^{2n+1} and is a retract of some neighborhood in R2n+1R^{2n+1}.

Let (M,ω)(M,ω) be a pseudo-Hermitian space of real dimension 2n+12n+1, that is $\RManBase$ is a $\CR-$manifold of dimension 2n+12n+1 and ωω is a contact form on MM giving the Levi distribution HT(M)TMHT(M)\subset TM. Let MωTMM^ω\subset T^*M be the canonical symplectization of (M,ω)(M,ω) and MM be identified with the zero section of …

2010-02-24abs ↗pdf ↗

We study a family of regularized score-based estimators for learning the structure of a directed acyclic graph (DAG) for a multivariate normal distribution from high-dimensional data with pnp\gg n. Our main results establish support recovery guarantees and deviation bounds for a family of penalized least-squares estima…

2015-11-29abs ↗pdf ↗

Adaptive framework improves nonparametric dimensionality reduction.

problem Optimal hyper-parameter tuning for nonparametric dimensionality reduction.
method Adaptive framework using intrinsic dimension estimator and optimal local neighbourhood sizes.
result Significant improvements in various learning tasks through better low-dimensional visualizations.

Nowadays, collaborative filtering recommender systems have been widely deployed in many commercial companies to make profit. Neighbourhood-based collaborative filtering is common and effective. To date, despite its effectiveness, there has been little effort to explore their robustness and the impact of data poisoning …

2019-12-01abs ↗pdf ↗

We introduce the natural and fairly general notion of a subanalytic bundle (with a finite dimensional vector space PP of sections) on a subanalytic subset XX of a real analytic manifold MM, and prove that when MM is compact, there is a Baire subset UU of sections in PP whose zero-loci in XX have tubular neighbou…

2003-07-02abs ↗pdf ↗

New method learns dependencies in high-dimensional data without graph assumptions.

problem Learning dependencies in nonparametric and high-dimensional settings.
method Neighbourhood lattice decomposition for nonparametric CI learning.
result Compact, non-graphical representation of CI exists in any graphical model.

We present in this paper a C1C^1-metric on an open neighbourhood of the origin in $\RR^{5}$. The metric is of Lorentzian signature (1,4)(1,4) and admits a solution to the twistor equation for spinors with a unique isolated zero at the origin. The metric is not conformally flat in any neighbourhood of the origin. The const…

2006-02-27abs ↗pdf ↗

This work proposes splitting deep neural networks into smaller sub-networks for faster and more efficient distillation.

problem Challenges in training deep neural networks, including local optima, gradient issues, and computational demands.
method Proposes a non-end-to-end distillation approach by splitting networks into smaller, independent sub-networks (neighbourhoods).
result Independent training of smaller sub-networks can speed up distillation and improve efficiency in various applications.

The paper generalizes hyperkahler metrics near Lagrangian submanifolds.

problem Constructing hyperkahler structures near complex Lagrangian submanifolds.
method Generalization of Feix-Kaledin theorem and deformations of holomorphic symplectic structures.
result Hyperkahler structures can be constructed on symplectic realizations of holomorphic Poisson manifolds.

The paper studies deformations of Lagrangian submanifolds using algebraic tools.

problem Deformation theory of Lagrangian submanifolds in symplectic geometry.
method Graded versions of the Darboux Theorem and Weinstein's Lagrangian tubular neighbourhood Theorem, attaching an LL_\infty-algebra to each submanifold.
result Controls the deformation theory of Lagrangian NQNQ-submanifolds using an LL_\infty-algebra.

Given a 2-crossing minimal chart ΓΓ, a minimal chart with two crossings, set α=min{ i  α=\min\{~i~|~there exists an edge of label ii containing a white vertex}\}, and β=max{ i  β=\max\{~i~|~there exists an edge of label ii containing a white vertex}\}. In this paper we study the structure of a neighbourhood of ΓαΓβΓ_α\cupΓ_β, and p…

2017-09-26abs ↗pdf ↗

We consider estimating the edge-probability matrix of a network generated from a graphon model when the full network is not observed---only some overlapping subgraphs are. We extend the neighbourhood smoothing (NBS) algorithm of Zhang et al. (2017) to this missing-data set-up and show experimentally that, for a wide ra…

2019-06-02abs ↗pdf ↗

The problem of determining the volume of a tubular neighbourhood has a long and rich history. Bounds on the volume of neighbourhoods of algebraic sets have turned out to play an important role in the probabilistic analysis of condition numbers in numerical analysis. We present a self-contained derivation of bounds on t…

2012-10-13abs ↗pdf ↗

Control data constructed for smooth weak deformation retraction of stratified spaces.

problem Construct control data for smooth weak deformation retraction of stratified spaces.
method Show smooth local triviality with conical fibers, construct control data, use fiber-wise scalar multiplications.
result Obtain neighbourhood smooth weak deformation retraction of stratified spaces.