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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.

168,694 papers · 148 categories

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20405979 · May 202619922001200920172026
48 results for piecewise-linear decomposition

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.

Recently Gay and Kirby described a new decomposition of smooth closed 44-manifolds called a trisection. This paper generalises Heegaard splittings of 33-manifolds and trisections of 44-manifolds to all dimensions, using triangulations as a key tool. In particular, we prove that every closed piecewise linear nn-mani…

2016-02-10abs ↗pdf ↗

In this note, we introduce a class of cell decompositions of PL manifolds and polyhedra which are more general than triangulations yet not as general as CW complexes; we propose calling them PLCW complexes. The main result is an analog of Alexander's theorem: any two PLCW decompositions of the same polyhedron can be ob…

2010-09-21abs ↗pdf ↗

Algorithm determines spatial graph isomorphism with vertex, edge colorings and orientations.

problem Algorithmic recognition of spatial graphs with various colorings and orientations.
method Proved existence of an algorithm for isomorphic spatial graphs, decomposed into canonical blocks, and applied Haken and Matveev's result.
result Algorithmic recognition of spatial graphs with colorings and orientations.

Gay and Kirby introduced the notion of a trisection of a smooth 4-manifold, which is a decomposition of the 4-manifold into three elementary pieces. Rubinstein and Tillmann later extended this idea to construct multisections of piecewise-linear (PL) manifolds in all dimensions. Given a PL manifold YY of dimension nn,…

2019-04-02abs ↗pdf ↗

The theory of geometric structures on a surface with nonempty boundary can be developed by using a decomposition of such a surface into hexagons, in the same way as the theory of geometric structures on a surface without boundary is developed using the decomposition of such a surface into pairs of pants. The basic elem…

2012-09-30abs ↗pdf ↗

On a K-unstable toric variety we show the existence of an optimal destabilising convex function. We show that if this is piecewise linear then it gives rise to a decomposition into semistable pieces analogous to the Harder-Narasimhan filtration of an unstable vector bundle. We also show that if the Calabi flow exists f…

2007-09-17abs ↗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 ↗

Discrete Morse functions induce shellings with critical tiles corresponding to function's critical faces.

problem Mapping discrete Morse functions to shellings for topological analysis.
method Inducing Morse shellings on the second barycentric subdivision of a simplicial complex.
result Critical tiles of induced shellings correspond to critical faces of the discrete Morse function.

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.

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 ↗

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 ↗

New proof shows efficient ReLU networks for piecewise linear functions.

problem Existence of efficient ReLU neural networks for piecewise linear functions.
method Degree 1 triangulations of the relative homology class bounded by polyhedra.
result Existence of efficient ReLU neural networks for functions with compact support.

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.

The paper tackles prescribing discrete Gaussian curvature on polyhedral surfaces.

problem Prescribing discrete Gaussian curvature on polyhedral surfaces.
method Discrete conformal theory and variational principles with constraints.
result Proves Kazdan-Warner type theorems for polyhedral surfaces.

Hilbert initiated the standpoint in foundations of mathematics. From this standpoint, we allow only a finite number of repetitions of elementary operations when we construct objects and morphisms. When we start from a subset of a Euclidean space. Then we assume that any element of the line has only a finite number of c…

2013-10-21abs ↗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 ↗

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.

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.

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 exhibit a knot PP in the solid torus, representing a generator of first homology, such that for any knot KK in the 3-sphere, the satellite knot with pattern PP and companion KK is not smoothly slice in any homology 4-ball. As a consequence, we obtain a knot in a homology 3-sphere that does not bound a piecewise-…

2014-05-06abs ↗pdf ↗

Simplifies PLNNs to interpretable models for better explainability.

problem Challenges in interpretability of PLNNs for high-stakes applications.
method Trained deep network simplification and algorithm for reducing flat networks.
result Improved interpretability of PLNNs without sacrificing performance.

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 ↗

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 consider the generic regularized optimization problem β^(λ)=argminβL(y,Xβ)+λJ(β)\hat{\mathsfβ}(λ)=\arg \min_βL({\sf{y}},X{\sfβ})+λJ({\sfβ}). Efron, Hastie, Johnstone and Tibshirani [Ann. Statist. 32 (2004) 407--499] have shown that for the LASSO--that is, if LL is squared error loss and J(β)=β1J(β)=\|β\|_1 is the 1\ell_1 norm of ββ--the opti…

2007-08-16abs ↗pdf ↗

The knot invariant Upsilon, defined by Ozsvath, Stipsicz, and Szabo, induces a homomorphism from the smooth knot concordance group to the group of piecewise linear functions on the interval [0,2]. Here we define a set of related secondary invariants, each of which assigns to a knot a piecewise linear function on [0,2].…

2016-10-17abs ↗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 ↗

SGD trains ReLU networks to implement piecewise linear maps with at most 3 knot points.

problem Understanding the training dynamics of neural networks trained via SGD.
method Mean-field analysis of a two-layer ReLU network trained via SGD for a univariate regression problem.
result At convergence, SGD-trained ReLU networks implement piecewise linear maps with at most 3 knot points.

There are 2^n possible resolutions of a smooth pseudodiagram with n precrossings. If we consider piecewise-linear (PL) pseudodiagrams and resolutions that themselves are PL, certain resolutions of the pseudodiagram may not exist in three-space. We investigate this situation and its impact on the weighted resolution set…

2013-08-30abs ↗pdf ↗

We present a new, unifying approach following some recent developments on the complexity of neural networks with piecewise linear activations. We treat neural network layers with piecewise linear activations as tropical polynomials, which generalize polynomials in the so-called (max,+)(\max, +) or tropical algebra, with pos…

2018-05-22abs ↗pdf ↗