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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 Normal rulings

We consider the Laplace normal vector field of relatively normalized ruled surfaces with non-vanishing Gaussian curvature in the three-dimensional Euclidean space R3\mathbb{R}^{3}. We determine all ruled surfaces and all relative normalizations for which the Laplace normal image degenerates into a point or into a curve…

2015-10-28abs ↗pdf ↗

This paper deals with skew ruled surfaces in the Euclidean space E3\mathbb{E}^{3} which are equipped with polar normalizations, that is, relative normalizations such that the relative normal at each point of the ruled surface lies on the corresponding polar plane. We determine the invariants of a such normalized ruled …

2017-11-29abs ↗pdf ↗

Defines and analyzes generalized normal ruled surfaces of curves in 3D space.

problem Understanding the geometry of generalized normal ruled surfaces.
method Calculates Gaussian and mean curvatures to determine surface properties and examines curve conditions.
result Determines when surfaces are flat or minimal and identifies specific curve types.

We consider relative normalizations of ruled surfaces with non-vanishing Gaussian curvature KK in the Euclidean space R3\mathbb{R} ^{3}, which are characterized by the support functions (α)q=Kα^{\left( α\right) }q=\left \vert K\right \vert ^α for αRα\in \mathbb{R} (Manhart's relative normalizations). All ruled surfaces for…

2015-10-30abs ↗pdf ↗

In this study, we give the relationships between the conical curvatures of ruled surfaces drawn by the unit vectors of the ruling, central normal and central tangent of a regular ruled surface in the Euclidean -space. We obtain the differential equations characterizing slant ruled surfaces and if the reference ruled su…

2013-11-27abs ↗pdf ↗

This paper deals with skew ruled surfaces Φ\varPhi in the Euclidean space E3\mathbb{E}^{3} which are right normalized, that is they are equipped with relative normalizations, whose support function is of the form q(u,v)=f(u)+g(u)vw(u,v)q(u,v) = \frac{f(u) + g(u)\, v}{w(u,v)}, where w2(u,v)w^2(u,v) is the discriminant of the first fundamental f…

2017-06-21abs ↗pdf ↗

We study some properties of decomposable exact Lagrangian cobordisms between Legendrian links in R3\mathbb{R}^3 with the standard contact structure. In particular, for any decomposable exact Lagrangian filling LL of a Legendrian link KK, we may obtain a normal ruling of KK associated with LL. We prove that the asso…

2015-12-26abs ↗pdf ↗

We consider a skew ruled surface ΦΦ in the Euclidean space E3E^{3} and relative normalizations of it, so that the relative normals at each point lie in the corresponding asymptotic plane of ΦΦ. We call such relative normalizations and the resulting relative images of ΦΦ \emph{asymptotic}. We determine all ruled surf…

2013-07-23abs ↗pdf ↗

The main purpose of this paper is to provide an infinite family of counter examples of the open problem mentioned in [2]. In particular, we present an infinite family of a particular Legendrian (4,(2n+5))(4,-(2n+5))-torus knot, for each n0n \geq 0, which has only 1 normal ruling, but do not satisfy the even number of clasps co…

2015-12-26abs ↗pdf ↗

Motivated by a number of recent investigations, we define and investigate the various properties of the ruled surfaces depend on three dimensional Lie groups with a bi-variant metric. We give useful results involving the characterizations of these ruled surfaces. Some special ruled surfaces such as normal surface, bino…

2015-03-09abs ↗pdf ↗

We consider hypersurfaces in the real Euclidean space Rn+1\mathbb{R}^{n+1} (n2n\geq2) which are relatively normalized. We give necessary and sufficient conditions a) for a surface of negative Gaussian curvature in R3\mathbb{R}^3 to be ruled, b) for a hypersurface of positive Gaussian curvature in Rn+1\mathbb{R}^{n+1} to be…

2014-04-07abs ↗pdf ↗

As a contribution to interpretable machine learning research, we develop a novel optimization framework for learning accurate and sparse two-level Boolean rules. We consider rules in both conjunctive normal form (AND-of-ORs) and disjunctive normal form (OR-of-ANDs). A principled objective function is proposed to trade …

2016-06-18abs ↗pdf ↗

Method measures weight similarity in neural networks using normalization and statistical inference.

problem Quantifying weight similarity in non-convex neural networks.
method Chain normalization rule and hypothesis-training-testing statistical inference.
result Weights of identical neural networks converge to similar local solutions.

In this paper, we define a new type of ruled surface called ruled surface by using the alternative frame of a base curve. Then, we study its differential geometric properties such as striction line, distribution parameter, fundamental forms, Gaussian and mean curvatures. Moreover, we find geodesic curvatures, normal cu…

2019-10-15abs ↗pdf ↗

The study examines singularities and geometric properties of surfaces derived from frontals with specific singular points.

problem Characterizing and understanding the singularities and geometric properties of surfaces formed by the singular loci of normal congruences of frontals with pure-frontal singular points.
method Characterizations of singularities in terms of geometric invariants of the initial frontal are provided for the normal ruled surface. Relations between certain singularities of focal surfaces and geometric properties of the frontal are also explored.
result Behavior of Gaussian curvature of focal surfaces of frontals with a 5/25/2-cuspidal edge is considered.

Pareto's 80/20 rule follows a Gaussian distribution with twice the mean standard deviation.

problem Understanding variations in the 80/20 rule across different contexts.
method Identifying the statistical distribution of the 80/20 rule and its variations.
result The 80/20 rule follows a Gaussian distribution with a standard deviation twice the mean.

The Chekanov-Eliashberg differential graded algebra of a Legendrian knot L is a rich source of Legendrian knot invariants, as is the theory of generating families. The set P(L) of homology groups of augmentations of the Chekanov-Eliashberg algebra is an invariant, as is a count of objects from the theory of generating …

2014-06-30abs ↗pdf ↗

New type of ruled surfaces studied with properties and examples.

problem Characterizing and understanding new types of ruled surfaces.
method Definition of a new orthonormal frame, calculation of Gaussian and mean curvatures, analysis of Weingarten map and geodesic properties.
result Conditions for an OT-surface to be flat or minimal are derived, and examples of helices and slant helices are provided.

A normal field on a spacelike surface in R14R^4_1 is called bi-normal if KνK^ν, the determinant of Weingarten map associated with νν, is zero. In this paper we give a relationship between the spacelike pseudo-planar surfaces and spacelike pseudo-umbilical surfaces, then study the bi-normal fields on spacelike ruled sur…

2013-01-05abs ↗pdf ↗

This paper improves bandwidth selectors for SPBNs to enhance their performance.

problem Suboptimal density estimation and reduced predictive performance in SPBNs due to normal rule bandwidth selection.
method Theoretical framework for state-of-the-art bandwidth selectors (cross-validation and plug-in methods) are established and evaluated.
result Cross-validation selectors outperform the normal rule, especially in high sample size scenarios.

This study examines geometric properties and offsets of slant timelike-ruled surfaces.

problem Geometric properties and offsets of slant timelike-ruled surfaces in Minkowski 3-space.
method Derivation of parametric formulation, conditions for coaxial alignment, examination through Blaschke and Darboux frames.
result Conditions ensuring the coaxial alignment of the central normal with the ruling direction of the offset surface.

Associated to Legendrian links in the standard contact three-space, Ruling polynomials are Legendrian isotopy invariants, which also compute augmentation numbers, that is, the points-counting of augmentation varieties for Legendrian links (up to a normalized factor) \cite{HR15}. In this article, we generalize this pict…

2017-07-16abs ↗pdf ↗

Paper explores Bayes rule for Gaussian mixtures with missing data, outperforming supervised classifiers.

problem Improving classification accuracy in partially classified samples with missing data.
method Generative model framework with missing-data mechanism, Bayes rule allocation.
result Bayes rule classifier with missing-data mechanism outperforms fully supervised classifiers in various conditions.

In this paper, we analyze the geometric structure of an Euclidean submanifold whose osculating spaces form a nonconstant family of proper subspaces of the same dimension. We prove that if the rate of change of the osculating spaces is small, then the submanifold must be a (submanifold of a) ruled submanifold of a very …

2011-05-04abs ↗pdf ↗

The paper introduces new portfolio rules beyond mean-variance, addressing asymmetry and uncertainty.

problem Optimizing portfolios with asymmetric returns and uncertainty in expected returns.
method Derives allocation rules for asymmetric Laplace distributed returns and random normal expected returns. Addresses singular covariance matrices and uncertainty in returns.
result Optimal worst-case scenario solution provides a convex alternative to risk parity, improving portfolio stability.

SOAR generates rules for both positive and negative classes in binary classification.

problem Lack of interpretability in machine learning models for binary classification.
method Extends or-of-and classification technique to both positive and negative classes.
result Competitive classification performance with simulated-annealing optimization.

New learning rules from information bottleneck improve deep learning without precise labels.

problem Training deep neural networks with backpropagation is biologically implausible.
method Kernelized information bottleneck principle with 3-factor Hebbian structure.
result The new learning rules perform nearly as well as backpropagation on image classification tasks.

New rules control false discoveries in online anomaly detection for time series data.

problem Controlling false discoveries in anomaly detection for time series data.
method Novel online false discovery rate control (FDRC) rules for time series anomaly detection.
result Ensures high power in detecting anomalies even when the alternative is rare and test statistics are serially dependent.

Despite their great success in recent years, deep neural networks (DNN) are mainly black boxes where the results obtained by running through the network are difficult to understand and interpret. Compared to e.g. decision trees or bayesian classifiers, DNN suffer from bad interpretability where we understand by interpr…

2019-07-01abs ↗pdf ↗

Paper classifies rational 3-tangles using normal forms and minimal coordinates.

problem Classifying rational 3-tangles up to isotopy.
method Defined normal form and normal coordinate, investigated minimal coordinates, constructed contractible simplicial complex.
result Simplicial complex of normal forms is contractible, leading to classification of rational 3-tangles.

Given a smooth curve γγ in some mm-dimensional surface MM in Rm+1\mathbb{R}^{m+1}, we study existence and uniqueness of a flat surface HH having the same field of normal vectors as MM along γγ, which we call a flat approximation of MM along γγ. In particular, the well-known characterisation of flat surfaces as to…

2018-12-03abs ↗pdf ↗

Unified framework for shrinkage, thresholding, and regularization in normal mean estimation and linear regression.

problem Estimation of normal mean in multivariate settings with correlated observations.
method Approximate risk minimization over a functional class of shrinkage-thresholding rules.
result Unified estimator NOMAD for shrinkage, thresholding, and regularization.

An online decision-making algorithm using stochastic gradient descent for big data.

problem Efficiently updating decision rules in online decision making with big data.
method Stochastic gradient descent for online updates, asymptotic normality of estimators.
result Asymptotic normality of parameter and value estimators, enabling statistical inference.

This paper proposes a new method to approximate posterior distributions using generative neural networks trained via scoring rule minimization.

problem Bayesian Likelihood-Free Inference for models with intractable likelihood.
method Approximate posterior with generative neural networks trained via scoring rule minimization, avoiding the instability of adversarial training.
result Scoring Rule minimization leads to better performance and uncertainty quantification compared to adversarial training.

In this paper, we study the spherical indicatrices of W-direction curves in three dimensional Euclidean space which were defined by using the unit Darboux vector field W of a Frenet curve, in [11]. We obtain the Frenet apparatus of these spherical indicatrix curves and the characterizations of being general helix and s…

2015-06-12abs ↗pdf ↗

For any Legendrian link, L, in (\R^3, \ker(dz-y\,dx)) we define invariants, Aug_m(L,q), as normalized counts of augmentations from the Legendrian contact homology DGA of L into a finite field of order q where the parameter m is a divisor of twice the rotation number of L. Generalizing a result of Ng and Sabloff for the…

2013-08-21abs ↗pdf ↗