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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.

168,657 papers · 148 categories

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3774110147 · Jun 202019922001200920172026
48 results for hyper-dual vectors

Study defines hyper-dual spheres and ruled surfaces, proving geometric relationships.

problem Understanding geometric properties of hyper-dual spheres and ruled surfaces.
method Defined hyper-dual spheres, developed ruled surfaces, and established geometric relationships.
result Proved isomorphism between hyper-dual sphere and tangent bundle, and geometric interpretation of ruled surfaces.

Speaker verification (SV) systems using deep neural network embeddings, so-called the x-vector systems, are becoming popular due to its good performance superior to the i-vector systems. The fusion of these systems provides improved performance benefiting both from the discriminatively trained x-vectors and generative …

2018-09-17abs ↗pdf ↗

The paper proves that certain modified conformal vector fields are trivial on compact and non-compact manifolds.

problem Proving triviality of modified conformal vector fields on Riemannian manifolds.
method Analyzing properties of homothetic, conformal, and gradient vector fields on compact and non-compact manifolds.
result Established conditions under which mm-modified conformal vector fields are trivial.

The position vector field x is the most elementary and natural geometric object on a Euclidean submanifold MM. The position vector field plays very important roles in mathematics as well as in physics. Similarly, the tangential component x^T of the position vector field is the most natural vector field tangent to the …

2017-12-24abs ↗pdf ↗

For a submanifold M in a Euclidean space, the tangential component x^T of the position vector field x of M is the most natural vector field tangent to the Euclidean submanifold, called the canonical vector field of M. In this article, first we prove that the canonical vector field of every Euclidean submanifold is alwa…

2018-01-22abs ↗pdf ↗

Study biharmonic vector fields and unit vector fields on Riemannian manifolds.

problem Determine the equivalence of biharmonicity and harmonicity for vector fields and unit vector fields on Riemannian manifolds.
method Analyze biharmonic vector fields and unit vector fields on (M,g)(M,g) with pseudo-Riemannian gg-natural metrics on TMTM and T1MT_1M.
result Contrary to Sasaki metric, biharmonicity and harmonicity are not equivalent for large classes of gg-natural metrics on TMTM.

This short report establishes some basic properties of smooth vector fields on product manifolds. The main results are: (i) On a product manifold there always exists a direct sum decomposition into horizontal and vertical vector fields. (ii) Horizontal and vertical vector fields are naturally isomorphic to smooth famil…

2011-06-05abs ↗pdf ↗

The paper bounds the mean absolute error in DNN vector-to-vector regression.

problem Bounding the mean absolute error in deep neural network based vector-to-vector regression.
method Error decomposition techniques in statistical learning theory and non-convex optimization theory were used to derive upper bounds for approximation, estimation, and optimization errors.
result Theoretical upper bounds for mean absolute error in DNN vector-to-vector regression were derived and validated experimentally.

Defines quaternionic k-vector fields on quaternionic Kähler manifolds.

problem No specific problem stated; focuses on definition and properties.
method Introduced a modified Dirac operator to define quaternionic k-vector fields.
result Calculated the dimension of quaternionic k-vector fields on HPn\mathbb{H}P^n.

SVM generalizes well even with many support vectors in high dimensions.

problem Generalization of SVM in high-dimensional spaces with many support vectors.
method Identified new deterministic equivalences and proved conditions for support vector proliferation.
result Broadened conditions for SVM generalization in high-dimensional settings and proved converse result.

Optimal transport for vector Gaussian mixtures improves efficiency and structure preservation.

problem Optimal mass transport for vector-valued Gaussian mixtures.
method Vectorizing Gaussian mixture models and studying optimal mass transport problems.
result Computational efficiency and structure preservation in optimal mass transport.

Study on vector fields on Lie groups reveals surprising algebraic coincidences.

problem Characterizing vector fields on Lie groups with Riemannian metrics.
method Algebraic and geometric analysis of left-invariant vector fields on nilpotent Lie groups.
result Spaces of Killing, one-harmonic, and conformal vector fields coincide with the center of the Lie algebra on nilpotent Lie groups.

This paper introduces \infty- and nn-fold vector bundles as special functors from the \infty- and nn-cube categories to the category of smooth manifolds. We study the cores and "n-pullbacks" of nn-fold vector bundles and we prove that any nn-fold vector bundle admits a non-canonical isomorphism to a decomposed …

2018-09-05abs ↗pdf ↗

Study on generalized derivations in polynomial vector fields Lie algebras.

problem Understanding generalized derivations in specific Lie sub-algebras of polynomial vector fields.
method Analysis of Lie sub-algebras containing constant and Euler vector fields, under specified conditions.
result Characterization of generalized derivations in the studied Lie sub-algebras.

Study on Einstein solitons with specific vector fields and their properties.

problem Characterizing Einstein solitons with gradient, solenoidal, or concircular vector fields.
method Explicitly express the function λ by gradient vector field V and deduce geometric properties under certain curvature conditions.
result Explicit expressions for λ and geometric properties of Einstein solitons.

Study of generalized vector bundles and their geometric tools.

problem Extension of differential geometric tools to infinite dimensional vector bundles.
method Analysis of automorphisms, frame bundle, connection 1-forms, and covariant derivatives in diffeological vector pseudo-bundles.
result Non-isomorphism between connection 1-forms and covariant derivatives in infinite dimensional cases.

The paper explores MAE as a loss function for DNN vector-to-vector regression, proving its advantages over MSE.

problem Improving loss function for deep neural network based vector-to-vector regression.
method Presenting performance bounds and new properties of MAE, deriving generalized upper bounds, and interpreting MAE as a Laplacian distribution.
result MAE is a more suitable loss function than MSE for DNN based vector-to-vector regression, especially when errors follow a Laplacian distribution.

Defines connections on parabolic vector bundles for Lie algebroids.

problem Characterizing parabolic vector bundles with Lie algebroid connections.
method Constructs Lie algebroid connections on parabolic vector bundles, uses Atiyah exact sequence.
result Characterizes stable Lie algebroid vector bundles with connections.

We explore under what conditions one can obtain a nontrivial knot, given a collection of nn vectors. First, we show how to get a crossing from any 3 vectors equal in magnitude, by arbitrarily picking 2 vectors and identifying the sufficient and necessary criteria for picking a third vector that will guarantee a crossi…

2016-12-20abs ↗pdf ↗

The paper proves non-existence of torqued and anti-torqued vector fields on hyperbolic spaces.

problem Existence of torqued and anti-torqued vector fields on hyperbolic spaces.
method Analyzing the properties of conformal scalar functions and their impact on the existence of vector fields.
result Non-existence of proper torqued and anti-torqued vector fields on hyperbolic spaces.

We introduce G_2-vector fields, Rochesterian 1-forms and Rochesterian vector fields on manifolds with a closed G_2-structure as analogues of symplectic vector fields, Hamiltonian functions and Hamiltonian vector fields respectively, and we show that the spaces of G_2-vector fields and of Rochesterian vector fields are …

2011-12-05abs ↗pdf ↗

The support vector machine (SVM) is an important class of learning machines for function approach, pattern recognition, and time-serious prediction, etc. It maps samples into the feature space by so-called support vectors of selected samples, and then feature vectors are separated by maximum margin hyperplane. The pres…

2016-02-12abs ↗pdf ↗

We describe two methods for showing that a vector can not be the f-vector of a homology d-ball. As a consequence, we disprove a conjectured characterization of the f-vectors of balls of dimension five and higher due to Billera and Lee. We also provide a construction of triangulated balls with various f-vectors. We show…

2009-12-10abs ↗pdf ↗

The paper extends positivity results from vector bundles to Kobayashi positive ones.

problem Extending positivity results from vector bundles to Kobayashi positive ones.
method Using convexity of Kobayashi positive Finsler metrics and duality for convex Finsler metrics.
result The quotient and tensor product of Kobayashi positive vector bundles are also Kobayashi positive.

The paper explores how vector fields relate to volume in geometric contexts.

problem Existence of nondiffeomorphic contact forms with identical Reeb vector fields.
method Analyzes geodesible vector fields and their associated Euler classes, applying topological and geometric theorems.
result Proves the Gauss-Bonnet and Poincaré-Hopf theorems for 2D orbifolds using geodesible vector fields.