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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.

169,181 papers · 148 categories

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113226338451 · Jun 202019922001200920182026
48 results for cutting number

The study provides bounds and necessary conditions for tunnel and cutting numbers of knots and handlebody-knots.

problem Determining bounds for tunnel and cutting numbers of knots and handlebody-knots.
method Using G-family of quandles colorings and constructing handlebody-knots.
result Lower bounds and necessary conditions for tunnel and cutting numbers of knots and handlebody-knots.

The cut number of a manifold M, c(M), is the largest number of disjoint two-sided hypersurfaces in M which do not separate M. Equivalently, it is the largest rank of a free group being an epimorphic image of pi_1(M). We investigate the relations between the cut number and the first Betti number, b_1(M), of 3-manifolds …

2001-12-12abs ↗pdf ↗

The question was raised as to whether the cut number of a 3-manifold X is bounded from below by 1/3 beta_1(X). We show that the answer to this question is `no.' For each m>0, we construct explicit examples of closed 3-manifolds X with beta_1(X)=m and cut number 1. That is, pi_1(X) cannot map onto any non-abelian free g…

2001-12-19abs ↗pdf ↗

Differentiable cutting-plane layers solve parametric mixed-integer linear optimization problems.

problem Solving parametric mixed-integer linear optimization problems with changing data.
method Introducing cutting-plane layers (CPLs) for differentiable cutting-plane generation.
result The algorithm computes solutions with low integrality gaps and generalizes to unseen instances.

Algorithms based on spectral graph cut objectives such as normalized cuts, ratio cuts and ratio association have become popular in recent years because they are widely applicable and simple to implement via standard eigenvector computations. Despite strong performance for a number of clustering tasks, spectral graph cu…

2014-10-29abs ↗pdf ↗

This paper establishes the consistency of a family of graph-cut-based algorithms for clustering of data clouds. We consider point clouds obtained as samples of a ground-truth measure. We investigate approaches to clustering based on minimizing objective functionals defined on proximity graphs of the given sample. Our f…

2014-11-24abs ↗pdf ↗

Study on limits and cut-off phenomena in deep neural networks.

problem Understanding the behavior of deep neural networks as the number of layers increases.
method Analysis of semi-invariant metrics and application of non-commutative ergodic theorems.
result Observation of a cut-off phenomenon in the number of layers for random network initialization.

Among all torus links, we characterise those arising as links of simple plane curve singularities by the property that their fibre surfaces admit only a finite number of cutting arcs that preserve fibredness. The same property allows a characterisation of Coxeter-Dynkin trees (i.e., AnA_n, DnD_n, E6E_6, E7E_7 and E8E_8

2014-09-02abs ↗pdf ↗

Generalizes neural network verification by adding arbitrary cutting planes.

problem Handling general cutting plane constraints in neural network verification.
method Generalized bound propagation method (GCP-CROWN) that allows arbitrary cutting plane constraints.
result GCP-CROWN significantly improves neural network verification performance.

We investigate Legendrian graphs in (R3,ξstd)(\R^3, ξ_{std}). We extend the classical invariants, Thurston-Bennequin number and rotation number to Legendrian graphs. We prove that a graph can be Legendrian realized with all its cycles Legendrian unknots with tb=1tb=-1 and rot=0rot=0 if and only if it does not contain K4K_4 as a mi…

2011-08-10abs ↗pdf ↗

Disk pairings with zero signature are related to topological surfaces.

problem Relating pairings with zero signature to topological surfaces.
method Cut-and-glue operations to transform pairings and prove connectivity.
result All balanced pairings for a fixed n are connected on a surface with any number of boundary components.

Binacox detects multiple cut-points in high-dimensional Cox models for genetic cancer data.

problem Detecting multiple cut-points in high-dimensional Cox models with many continuous features.
method Combines one-hot encoding with binarsity penalty for feature selection and regularization.
result Significantly outperforms state-of-the-art survival models in terms of C-index and computational speed.

This paper studies the large sample asymptotics of data analysis procedures based on the optimization of functionals defined on kk-NN graphs on point clouds. The paper is framed in the context of minimization of balanced cut functionals, but our techniques, ideas and results can be adapted to other functionals of rele…

2016-07-03abs ↗pdf ↗

In the present paper we give a proof of the fact that the sub-Riemannian cut locus of a wide class of nilpotent groups of step two, called HH-type groups, starting from the origin corresponds to the center of the group. We obtain this result by completely describing the sub-Riemannian geodesics in the group, and using…

2014-10-09abs ↗pdf ↗

We determine the set of all genus g bridge numbers of many iterated torus knots, listing these numbers in a sequence called the bridge spectrum. In addition, we prove a structural lemma about the decomposition of a strongly irreducible bridge surface induced by cutting along a collection of essential surfaces.

2013-01-31abs ↗pdf ↗

In this paper we construct explicit examples of both closed and non-compact finite volume hyperbolic manifolds which provide counterexamples to the conjecture that the co-rank of a 3-manifold group (also known as the cut number) is bounded below by one-third the first Betti number.

2002-02-25abs ↗pdf ↗

NeuralCut learns to select cutting planes by looking ahead, outperforming traditional methods.

problem Selecting effective cutting planes for MILP optimization.
method Imitation learning on a lookahead expert to train a neural network for cut selection.
result NeuralCut outperforms standard baselines in cut selection for MILP benchmarks.

NeVI-Cut uses neural networks to efficiently propagate uncertainty without feedback.

problem Efficiently propagating uncertainty in downstream Bayesian analysis without feedback.
method NeVI-Cut combines neural networks and normalizing flows for variational inference.
result NeVI-Cut achieves significant computational gains and higher accuracy than traditional methods.

Paper connects probability density cuts to graph theory eigenfunctions.

problem Developing sparse cuts for probability densities.
method Defines sparse cuts and principal eigenfunctions for probability densities, proving Cheeger and Buser inequalities.
result No such inequalities hold for prior definitions, proving new inequalities for probability densities.

Stability of cut locus under metric perturbations in compact Riemannian manifolds.

problem Stability of cut locus under C2C^2-perturbations of the metric.
method Proving stability with respect to the Hausdorff metric of the cut locus under C2C^2 perturbation of the metric.
result The Hausdorff distance between cut loci converges to zero as the metrics converge.

Improved reasoning model by sampling from power distribution without additional training.

problem Efficiently sampling from a sharpened distribution to improve reasoning models.
method Entropy-Cut Metropolis-Hastings algorithm that identifies key decision points for resampling.
result The method consistently improves reasoning models across various datasets.

Study on mapping classes of real rational surface automorphisms, focusing on reducible maps and pseudo-Anosov maps.

problem Investigating the mapping classes of real rational surface automorphisms and their restrictions.
method Analysis of reducible maps, determination of pseudo-Anosov mapping classes, and comparison with Penner's construction.
result Realized Lehmer's number as the stretch factor of a pseudo-Anosov map on a specific surface.

We consider the problem of classifying data manifolds where each manifold represents invariances that are parameterized by continuous degrees of freedom. Conventional data augmentation methods rely upon sampling large numbers of training examples from these manifolds; instead, we propose an iterative algorithm called M…

2017-05-28abs ↗pdf ↗

Study shows convergence rates for Cheeger cuts on data clouds.

problem Optimizing graph cuts for clustering data sampled from a manifold.
method Analyzes statistical properties of Cheeger cuts on proximity graphs built from data.
result Obtains high probability convergence rates for Cheeger constant and cuts.