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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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121241362482 · Jun 202019922001200920172026
48 results for piecewise linear embedding

We study piecewise linear co-dimension two embeddings of closed oriented manifolds in Euclidean space, and show that any such embedding can always be isotoped to be a closed braid as long as the ambient dimension is at most five, extending results of Alexander (in ambient dimension three), and Viro and independently Ka…

2017-03-24abs ↗pdf ↗

A triangulated piecewise-linear minimal surface in Euclidean 3-space defined using a variational characterization is critical for area amongst all continuous piecewise-linear variations with compact support that preserve the simplicial structure. We explicitly construct examples of such surfaces that are embedded and a…

2004-10-13abs ↗pdf ↗

We demonstrate new applications of the trace embedding lemma to the study of piecewise-linear surfaces and the detection of exotic phenomena in dimension four. We provide infinitely many pairs of homeomorphic 4-manifolds WW and WW' homotopy equivalent to S2S^2 which have smooth structures distinguished by several for…

2019-12-30abs ↗pdf ↗

We obtain a criterion for approximability by embeddings of piecewise linear maps of a circle to the plane, analogous to the one proved by Minc for maps of a segment to the plane. Theorem. Let S be a triangulation of a circle with s vertices. Let f be a simplicial map of the graph S to the plane. The map f is approximab…

2008-08-08abs ↗pdf ↗

This paper considers affine analogues of the isoperimetric inequality in the sense of piecewise linear topology. Given a closed polygon P embedded in R^d having n edges, we give upper and lower bounds for the minimal number of triangles needed to forma triangulated embedded orientable surface in R^d having P as its geo…

2002-02-18abs ↗pdf ↗

We introduce a new multi-dimensional nonlinear embedding -- Piecewise Flat Embedding (PFE) -- for image segmentation. Based on the theory of sparse signal recovery, piecewise flat embedding with diverse channels attempts to recover a piecewise constant image representation with sparse region boundaries and sparse clust…

2018-02-09abs ↗pdf ↗

We develop a new approach to the classical problem on isotopy classification of embeddings of manifolds into Euclidean spaces. This approach involves studying of a new embedding invariant, of almost-embeddings and of smoothing, as well as explicit constructions of embeddings. Using this approach we obtain complete conc…

2006-07-18abs ↗pdf ↗

This paper introduces a new method to better understand financial market causality.

problem Lack of comprehensive understanding of distributional causality in financial markets.
method Combines piecewise quantile regression with a piecewise linear embedding scheme.
result Uncovered significant tail-tail causal effects and substantial causal asymmetry in cryptocurrency return series.

Algorithm identifies best arm in piecewise stationary linear bandits with minimal samples.

problem Identifying the best arm in a piecewise stationary linear bandit model with unknown contexts and changepoints.
method Design of PSε\varepsilonBAI+^+ algorithm, consisting of PSε\varepsilonBAI and Nε\varepsilonBAI subroutines.
result PSε\varepsilonBAI+^+ achieves optimal sample complexity up to a logarithmic factor.

Piecewise flat approximations for curvature in Euclidean and non-Euclidean spaces.

problem Approximating local extrinsic curvature on discrete manifolds.
method Constructing discrete curvature forms on piecewise flat manifolds, using weighted sums of hinge angles.
result Converges to smooth curvature values as mesh refinement occurs, favorably comparing with other discrete approaches.

Let KK be a closed polygonal curve in $\RR^3$ consisting of nn line segments. Assume that KK is unknotted, so that it is the boundary of an embedded disk in $\RR^3$. This paper considers the question: How many triangles are needed to triangulate a Piecewise-Linear (PL) spanning disk of KK? The main result exhibits …

1999-06-28abs ↗pdf ↗

The paper proposes new cross-correlators using Price's Theorem and piecewise-linear decomposition.

problem Optimal method for estimating cross-correlations using finite samples.
method General mathematical framework using Price's Theorem and piecewise-linear decomposition.
result Some cross-correlators based on Huber's loss functions, MP functions, and LSE functions have higher SNR.

We construct infinitely many smooth 4-manifolds which are homotopy equivalent to S2S^2 but do not admit a spine, i.e., a piecewise-linear embedding of S2S^2 which realizes the homotopy equivalence. This is the remaining case in the existence problem for codimension-2 spines in simply-connected manifolds. The obstructio…

2018-03-05abs ↗pdf ↗

This article provides an attempt to extend concepts from the theory of Riemannian manifolds to piecewise linear spaces. In particular we propose an analogue of the Ricci tensor, which we give the name of an Einstein vector field. On a given set of piecewise linear spaces we define and discuss (normalized) Ricci flows. …

2015-08-22abs ↗pdf ↗

We prove that every piecewise linear manifold of dimension up to four on which a finite group acts by piecewise linear homeomorphisms admits a compatible smooth structure with respect to which the group acts smoothly. This solves a challenge posed by Thurston in dimension three and confirms a conjecture by Kwasik and L…

2015-07-09abs ↗pdf ↗

Piecewise linear activations create many spurious local minima in neural networks.

problem Understanding the loss surface of neural networks with piecewise linear activations.
method Proved the existence of infinite spurious local minima and partitioned the loss surface into smooth cells.
result Piecewise linear activations create many spurious local minima that are invariant under a continuous path.

The paper extends a variance gamma model to quadratic functions, reducing arbitrage and computational costs.

problem Creating an arbitrage-free interpolation for option pricing models.
method Generalizing the local variance gamma model to a piecewise quadratic local variance function.
result The quadratic model results in an arbitrage-free interpolation of class C3, reducing knots and computational cost.

We define an isotopy invariant of embeddings N -> R^m of manifolds into Euclidean space. This invariant together with the α-invariant of Haefliger-Wu is complete in the dimension range where the α-invariant could be incomplete. We also define parametric connected sum of certain embeddings (analogous to surgery). This a…

2005-09-27abs ↗pdf ↗

Let XX be a simplicial complex with a piecewise linear function f:XRf:X\to\mathbb{R}. The Reeb graph Reeb(f,X)Reeb(f,X) is the quotient of XX, where we collapse each connected component of f1(t)f^{-1}(t) to a single point. Let the nodes of Reeb(f,X)Reeb(f,X) be all homologically critical points where any homology of the corresponding c…

2013-12-05abs ↗pdf ↗

In this paper, we introduce a bordism category CdPL\mathcal{C}_d^{PL} whose objects are bundles of closed (d1)(d-1)-dimensional piecewise linear manifolds and whose morphisms are bundles of dd-dimensional piecewise linear cobordisms. In the main theorem of this article, we show that the classifying space $B\mathcal{C}_d^{…

2016-08-22abs ↗pdf ↗

We propose learning deep models that are monotonic with respect to a user-specified set of inputs by alternating layers of linear embeddings, ensembles of lattices, and calibrators (piecewise linear functions), with appropriate constraints for monotonicity, and jointly training the resulting network. We implement the l…

2017-09-19abs ↗pdf ↗

New GP model estimates piecewise continuous functions.

problem Piecewise continuous regression functions in scientific and engineering applications.
method Local Gaussian process model with partitioned local data and joint estimation of boundaries.
result Superior performance over conventional GP models in estimating piecewise regression functions.

New method uses DC functions for piecewise linear regression.

problem Regression with piecewise linear constraints.
method Estimates piecewise linear convex functions using a difference of convex functions.
result Method achieves close to minimax statistical risk and comparable performance to existing methods.

Equivariant neural networks use symmetry to interpret complex data.

problem Interpreting and understanding the behavior of equivariant neural networks.
method Decompose layers into simple representations and analyze nonlinear activation functions.
result Equivariant neural networks can be interpreted using a filtration generalizing Fourier series.

A new complexity measure for neural networks improves upon classical methods.

problem Lack of a refined complexity measure for comparing different neural network architectures, especially permutation-invariant ones.
method Introduced an equivalence relation among linear functions and counted them relative to this relation.
result The new complexity measure clearly distinguishes between different models and increases exponentially with depth.

We study stable commutator length (scl) in free products via surface maps into a wedge of spaces. We prove that scl is piecewise rational linear if it vanishes on each factor of the free product, generalizing the main result in Danny Calegari's paper "Scl, sails and surgery". We further prove that the property of isome…

2016-11-22abs ↗pdf ↗

We present a detailed analysis of the class of regression decision tree algorithms which employ a regulized piecewise-linear node-splitting criterion and have regularized linear models at the leaves. From a theoretic standpoint, based on Rademacher complexity framework, we present new high-probability upper bounds for …

2019-06-29abs ↗pdf ↗

Paper presents ABGD for efficient piecewise linear regression in high dimensions.

problem Efficiently solving piecewise linear regression in high-dimensional spaces.
method Parametrizes piecewise linear functions as difference of max-affine functions, using ABGD algorithm.
result ABGD converges linearly to an ε-accurate estimate with optimal sample complexity.

We consider smooth isotropic immersions from the 2-dimensional torus into R2nR^{2n}, for n2n \geq 2. When n=2n = 2 the image of such map is an immersed Lagrangian torus of R4R^4. We prove that such isotropic immersions can be approximated by arbitrarily C0C^0-close piecewise linear isotropic maps. If n3n \geq 3 the piece…

2018-02-23abs ↗pdf ↗