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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.

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48 results for strong shape equivalence

Coarse homotopy theory connects Euclidean cones to shape theory of compact spaces.

problem Establishing connections between coarse homotopy theory and shape theory.
method Using pointed shape invariants and inverse mapping telescopes.
result Proving two compact spaces are strong shape equivalent if their Euclidean cones are coarsely homotopy equivalent.

Fine shape of local compacta represented by ordinary maps.

problem Representing fine shape of local compacta.
method Constructing a space X|X| for each local compactum XX such that fine shape classes correspond to homotopy classes of maps to X|X|.
result Fine shape classes from any locally compact metrizable space YY to XX bijectively correspond to homotopy classes of maps from YY to X|X|.

An algorithm preserves topological features in dimensionality reduction.

problem Preserving topological features in dimensionality reduction.
method Simulated annealing for finding a linear projection preserving persistent homology.
result Measures of topological equivalence between filtrations.

The paper shows how to use fine shape to understand infinite-dimensional spaces.

problem Understanding infinite-dimensional metrizable spaces and their homology theories.
method Obtained results indicating fine shape is tractable and can be used for Polish spaces.
result Every Polish space is fine shape equivalent to the limit of an inverse sequence of simplicial maps.

We introduce and develop fine shape, which has a very simple definition and aims to supersede all previously known shape theories for metrizable spaces. The problem with known shape theories of metrizable spaces is illustrated by the following bizarre situation. Čech cohomology is an invariant of shape, and a fortiori …

2018-08-30abs ↗pdf ↗

SVarM uses varifold representations for shape classification and regression.

problem Challenges in analyzing geometric data due to non-Euclidean shape spaces.
method Develops a neural network-based framework for varifold representations of shapes.
result Demonstrates strong performance and robustness in shape classification and regression.

M. Bestvina has shown that for any given torsion-free CAT(0) group G, all of its boundaries are shape equivalent. He then posed the question of whether they satisfy the stronger condition of being cell-like equivalent. In this article we prove that the answer is "Yes" in the situation where the group in question splits…

2007-07-29abs ↗pdf ↗

A recent Cell paper [Chang and Tsao, 2017] reports an interesting discovery. For the face stimuli generated by a pre-trained active appearance model (AAM), the responses of neurons in the areas of the primate brain that are responsible for face recognition exhibit strong linear relationship with the shape variables and…

2018-05-14abs ↗pdf ↗

A new method for analyzing shapes and forms using additive models on manifolds.

problem Analyzing shapes and forms under geometric transformations.
method Extending generalized additive regression to models for shapes/forms using squared geodesic distance and Riemannian L2L_2-Boosting algorithm.
result Automated model selection and intuitive visualization of covariate effects in shape/form space.

Any subset of the plane can be approximated by a set of square pixels. This transition from a shape to its pixelation is rather brutal since it destroys geometric and topological information about the shape. Using a technique inspired by Morse Theory, we algorithmically produce a PL approximation of the original shape …

2011-05-13abs ↗pdf ↗

Study confirms equivalence in Heisenberg groups between curvature-dimension conditions and strong Brunn-Minkowski inequalities.

problem Equivalence between curvature-dimension conditions and strong Brunn-Minkowski inequalities in Heisenberg groups.
method Optimal transport and approximation techniques in sub-Riemannian Heisenberg group Hn, combined with previous works.
result Confirms the equivalence in Heisenberg groups between curvature-dimension conditions and strong Brunn-Minkowski inequalities.

The paper defines a new equivalence relation for knot projections and finds an infinite number of distinct classes.

problem Classifying knot projections based on weak homotopy equivalence.
method Defining weak (1, 2, 3) homotopy and using it to find an invariant.
result There are an infinite number of weak (1, 2, 3) homotopy equivalence classes of knot projections.

Self-training in linear models shows a U-shaped test-risk curve due to signal forgetting and denoising.

problem Understanding the dynamics of iterative self-training in high-dimensional linear regression.
method Derivation of deterministic-equivalent recursions for prediction risk and effective noise, analysis of signal forgetting and denoising effects.
result An optimal early-stopping time is determined, and a U-shaped test-risk curve is observed.

The classification of shapes is of great interest in diverse areas ranging from medical imaging to computer vision and beyond. While many statistical frameworks have been developed for the classification problem, most are strongly tied to early formulations of the problem - with an object to be classified described as …

2019-01-22abs ↗pdf ↗

It is known that shape injectivity implies homotopical Hausdorff and that the converse does not hold, even if the space is required to be a Peano continuum. This paper gives an alternative definition of homotopical Hausdorff inspired by a new topology on the set of fixed endpoint homotopy classes of paths. This version…

2011-04-05abs ↗pdf ↗

The paper defines new homotopy relations on knot projections and classifies certain knot types.

problem Defining and classifying knot homotopy relations.
method Introducing cross chord numbers and using them to define strong and weak (1, 3) homotopies.
result Complete classification of knot projections with trivializing number two.

Recently Swatee Naik and Theodore Stanford proved that two S-equivalent knots are related by a finite sequence of doubled-delta moves on their knot diagrams. We show that classical S-equivalence is not sufficient to extend their result to ordered links. We define a new algebraic relation on Seifert matrices, called Str…

2004-09-22abs ↗pdf ↗

This paper proposes the adaptation of Support Vector Data Description (SVDD) to the multiple kernel case (MK-SVDD), based on SimpleMKL. It also introduces a variant called Slim-MK-SVDD that is able to produce a tighter frontier around the data. For the sake of comparison, the equivalent methods are also developed for O…

2017-12-07abs ↗pdf ↗

Homotopy theory of differentiable sheaves connects manifold properties to underlying homotopy types.

problem Understanding the homotopy type of manifolds using differentiable sheaves.
method Developed model structures and homotopical calculi on the \infty-category Diff\mathbf{Diff}^\infty to compute and compare shapes.
result The shape of any manifold coincides with various other notions of underlying homotopy types.

Let MM be a manifold or (more generally) a locally compact, metrizable ANR. If KK is an attractor for a flow in MM, with basin of attraction A(K)\mathcal{A}(K), it is well known that the inclusion i:KA(K)i : K \subseteq \mathcal{A}(K) is always a shape equivalence. In this paper we investigate to what extent this generaliz…

2015-11-20abs ↗pdf ↗

This paper connects monetary and star-shaped risk measures by showing their equivalence under certain conditions.

problem Understanding the relationship between monetary and star-shaped risk measures.
method Analyzing the acceptability of 0 and the normalization property.
result Monetary risk measures are only a translation away from star-shapedness under mild conditions.

In 2000, Croke and Kleiner showed that a CAT(0) group G can admit more than one boundary. This contrasted with the situation for word hyperbolic groups, where it was well-known that each such group admitted a unique boundary---in a very stong sense. Prior to Croke and Kleiner's discovery, it had been observed by Geoghe…

2010-11-05abs ↗pdf ↗

New method simplifies checking consistency of differentiable loss functions.

problem Verifying consistency of differentiable loss functions is difficult.
method Developed a new approach called strong indirect elicitation (strong IE) to simplify checking consistency.
result Strong IE is equivalent to calibration for strongly convex, differentiable surrogates.

We present and study a family of metrics on the space of compact subsets of RNR^N (that we call ``shapes''). These metrics are ``geometric'', that is, they are independent of rotation and translation; and these metrics enjoy many interesting properties, as, for example, the existence of minimal geodesics. We view our s…

2007-07-09abs ↗pdf ↗

Given a TQFT in dimension d+1, and an infinite cyclic covering of a closed (d+1)-dimensional manifold M, we define an invariant taking values in a strong shift equivalence class of matrices. The notion of strong shift equivalence originated in R. Williams' work in symbolic dynamics. The Turaev-Viro module associated to…

1997-12-02abs ↗pdf ↗

DNAMite creates interpretable, calibrated survival analysis models.

problem Limited interpretability in survival analysis models, especially for healthcare applications.
method Feature discretization and kernel smoothing in embedding module for flexible shape functions.
result DNAMite produces calibrated shape functions interpretable as contributions to cumulative incidence function.

We analyze a monetary system of random money transfer on the basis of double entry bookkeeping. Without boundary conditions, we do not reach a price equilibrium and violate text-book formulas of economists quantity theory (MV=PQ). To match the resulting quantity of money with the model assumption of a constant price, w…

2002-11-06abs ↗pdf ↗

The purpose of this paper is to introduce a concept of equivalence between machine learning algorithms. We define two notions of algorithmic equivalence, namely, weak and strong equivalence. These notions are of paramount importance for identifying when learning prop erties from one learning algorithm can be transferre…

2014-06-10abs ↗pdf ↗

Recent reinforcement learning (RL) approaches have shown strong performance in complex domains such as Atari games, but are often highly sample inefficient. A common approach to reduce interaction time with the environment is to use reward shaping, which involves carefully designing reward functions that provide the ag…

2019-03-05abs ↗pdf ↗

This paper provides a topological method for filling contact structures on the connected sums of S2×S3S^2\times S^3. Examples of nonsymplectomorphic strong fillings of homotopy equivalent contact structures with vanishing first Chern class on #kS2×S3\#_k S^2\times S^3 (k2)(k\geq2) are produced.

2015-06-28abs ↗pdf ↗

Study of panhandle polynomials of torus links with geometric applications.

problem Characterizing the HOMFLY-PT polynomial of torus knots and links.
method Utilizing quantum group representations and the Rosso-Jones formula.
result Established panhandle-like structure of HOMFLY-PT polynomials for torus knots and links.

We study metrics on shape space of immersions that have a particularly simple horizontal bundle. More specifically, we consider reparametrization invariant Sobolev metrics GG on the space Imm(M,N)\operatorname{Imm}(M,N) of immersions of a compact manifold MM in a Riemannian manifold (N,g)(N,\overline{g}). The tangent space $T…

2014-03-06abs ↗pdf ↗

The study proves strong cosmic censorship violation for spherically symmetric dust clouds.

problem Violation of strong cosmic censorship for spherically symmetric dust clouds.
method Derived an ordinary differential equation for light rays and used it to prove strong cosmic censorship violation.
result Generic violation of strong cosmic censorship for spherically symmetric dust clouds.

Research on mixed polynomials, extending non-degeneracy concepts to complex variables.

problem Extending non-degeneracy concepts to mixed polynomials in complex variables.
method Generalization of Mondal's partial non-degeneracy to mixed polynomials, introducing new concepts and proving properties.
result Strong partial non-degeneracy implies isolated singularities, and mixed polynomials that are strongly inner non-degenerate satisfy the strong Milnor condition.

The study proves a strong parametric h-principle for minimal surfaces.

problem Proving a parametric h-principle for minimal surfaces.
method Using a parametric h-principle due to Forstneric and Larusson.
result The space of complete nonflat conformal minimal immersions has the same homotopy type as the space of continuous maps.

The paper explores a new method for landmark matching using sub-Riemannian geometry and neural networks.

problem Finding a time-dependent vector field to warp points from an initial set to a target set.
method Sub-Riemannian geometry and residual neural networks.
result Demonstrates the importance of regularization in landmark matching.