Research
On-device research index

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

Trend · papers per month

4998147196 · Jun 202019922001200920172026
48 results for Vector Decomposition

New ff-vectors reveal geometric Lefschetz-like decompositions of flag spheres.

problem Understanding ff-vectors of balanced simplicial complexes and flag spheres.
method Analyzing hh-vectors and ff-vectors of flag spheres and balanced simplicial complexes.
result Found ff-vectors leading to geometric Lefschetz-like decompositions.

The paper proposes and discusses semiorthogonal decompositions for moduli spaces of vector bundles.

problem Decompositions of moduli spaces of vector bundles with fixed determinant of odd degree.
method Semiorthogonal decompositions, Grothendieck ring of varieties, mirror symmetry, graph potentials, Fukaya category.
result Evidence for a conjectural semiorthogonal decomposition of moduli spaces of rank 2 bundles with odd determinant.

The main result is the identification of the orthogonal complement of the subalgebra of conformal vector field inside the algebra of all vector fields of a compact flat 2-manifold. As a fundamental tool, the complete Hodge decomposition for manifold with boundary is used. The identification allows the derivation of gov…

2012-03-20abs ↗pdf ↗

In this text we give a decomposition result on polynomial poly-vector fields generalizing a result on the decomposition of homogeneous Poisson structures. We discuss consequences of this decomposition result in particular for low dimensions and low degrees. We provide the tools to calculate simple cubic Poisson structu…

2004-09-09abs ↗pdf ↗

In this paper, we study face vectors of simplicial posets that are the face posets of cell decompositions of topological manifolds without boundary. We characterize all possible face vectors of simplicial posets whose geometric realizations are homeomorphic to the product of spheres. As a corollary, we obtain the chara…

2010-10-02abs ↗pdf ↗

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 ↗

New method preserves topology in Hodge decomposition for scalar and vector fields.

problem Topology-preserving Hodge decomposition on manifolds with boundaries.
method Comprehensive 5-component decomposition in Eulerian representation.
result Effective numerical experiments validate the method's accuracy and orthogonality.

New splitting theorems in a semi-Riemannian manifold which admits an irrotational vector field (not necessarily a gradient) with some suitable properties are obtained. According to the extras hypothesis assumed on the vector field, we can get twisted, warped or direct decompositions. Some applications to Lorentzian man…

2003-06-24abs ↗pdf ↗

The paper extends orthogonal decomposition results to hermitian Higgs bundles.

problem Classical propositions on holomorphic vector bundles do not always extend to Higgs bundles.
method The approach involves extending propositions on orthogonal decompositions and the second fundamental form to hermitian Higgs bundles.
result Extended propositions concerning orthogonal decompositions and the second fundamental form have applications in Higgs bundles.

The purpose of this paper is to describe certain natural 4-vector fields on quaternionic flag manifolds, which geometrically determine the Bruhat cell decomposition. This structure naturally descends from the symplectic group, where it is related to the dressing action given by the Iwasawa decomposition of the general …

2001-04-09abs ↗pdf ↗

Sparse Tucker decomposition with graph regularization improves time series forecasting accuracy.

problem High-dimensional time series forecasting with over-parameterization issue.
method Sparse Tucker decomposition and graph regularization for tensor-based model.
result Non-asymptotic error bound and superior performance in numerical experiments.

Bayesian approach approximates probability functions of Gaussian mixtures.

problem Approximating probability functions of non-spherical Gaussian mixtures.
method Bayesian decomposition, spherical radial decomposition, random sampling.
result Established differentiability and integral representation of gradient for probability functions.

We present an algebraic investigation of generalized and equiaffine curvature tensors in a given pseudo-Euclidean vector space and study different orthogonal, irreducible decompositions in analogy to the known decomposition of algebraic curvature tensors. We apply the decomposition results to characterize geometric pro…

2009-03-30abs ↗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.

Computes the decomposition of rank-three bundles over the projective line with three marked points.

problem Decomposing rank-three bundles over the projective line with three marked points.
method Using the monodromy derivative to compute the roots of the bundles.
result Computes the exact decomposition of rank-three bundles for m=3m = 3.

New algorithms improve tensor CP decomposition under mild conditions.

problem Improving tensor CP decomposition with theoretical guarantees under mild incoherence conditions.
method Composite PCA and Concurrent Orthogonalization algorithms.
result Theoretical guarantees and practical superiority over existing methods.

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 classifies and describes translators in SL(2,R)SL(2,\mathbb{R}) under specific symmetry conditions.

problem Classifying translators in SL(2,R)SL(2,\mathbb{R}) under invariant symmetry groups.
method Analyzing translators invariant by one-parameter groups of isometries, using Iwasawa decomposition and Killing vector fields.
result Explicit parametrizations of translators are obtained for some cases.

The study examines vector fields with integer singularities in 3D balls.

problem Characterizing the strong LpL^p-closure of vector fields with finitely many integer singularities.
method Characterization and decomposition of vector fields with finitely many integer singularities.
result Decomposition theorem for elements in LZ1(B)L_{\mathbb{Z}}^1(B), revealing information about mass-minimizing currents.

Word embedding is a powerful tool in natural language processing. In this paper we consider the problem of word embedding composition \--- given vector representations of two words, compute a vector for the entire phrase. We give a generative model that can capture specific syntactic relations between words. Under our …

2019-02-02abs ↗pdf ↗

The paper explores geometric decompositions for Ricci tensors and their applications.

problem Understanding Ricci tensors on compact Riemannian manifolds.
method Utilizes Berger-Ebin and York L2L^2-orthogonal decompositions.
result New insights into Ricci almost solitons and harmonic maps.

Generalizes randomized SVD for better matrix approximations using Gaussian vectors.

problem Computing accurate rank-k approximations of matrices with limited data.
method Extends randomized SVD to multivariate Gaussian vectors, incorporating prior knowledge and using Gaussian processes.
result Demonstrates improved accuracy in approximating matrices and Hilbert-Schmidt operators.

Data-aware methods for dimensionality reduction and matrix decomposition aim to find low-dimensional structure in a collection of data. Classical approaches discover such structure by learning a basis that can efficiently express the collection. Recently, "self expression", the idea of using a small subset of data vect…

2015-05-04abs ↗pdf ↗

In this paper, we consider a connected Riemannian manifold MM where a connected Lie group GG acts effectively and isometrically. Assume Xg=Lie(G)X\in\mathfrak{g}=\mathrm{Lie}(G) defines a bounded Killing vector field, we find some crucial algebraic properties of the decomposition X=Xr+XsX=X_r+X_s according to a Levi decompositio…

2019-04-18abs ↗pdf ↗

The paper develops algorithms and topological invariants for distinguishing dynamic systems.

problem Distinguishing the topological type of surfaces and functions in dynamic systems.
method Construction of algorithms and topological invariants using discrete topological structures.
result The development of discrete topological structures for topological equivalence of dynamic systems.

The paper studies posets from decompositions in symmetric monoidal categories.

problem Understanding posets from decompositions in symmetric monoidal categories.
method Defining decompositions and partial decompositions, complexes of frames, partial bases, and ordered versions.
result Unified approach to combinatorics and homotopy type of posets and complexes.

Study examines stability of MOTS in symmetric initial data sets.

problem Stability of marginally outer trapped surfaces in symmetric initial data sets.
method Characterizes instability through vector decomposition and properties of normal and tangent components.
result Characterizes instability of MOTS by the nature of zero sets and divergences.

We classify static manifolds which admit more than one static decomposition whenever a condition on the curvature is fullfilled. For this, we take a standard static vector field and analyze its associated one parameter family of projections onto the base. We show that the base itself is a static manifold and the warpin…

2009-10-26abs ↗pdf ↗

Several intrinsic topological ways to encode connections on vector bundles on smooth complex algebraic curves will be described. In particular the notion of {\em Stokes decompositions} will be formalised, as a convenient intermediate category between the Stokes filtrations and the Stokes local systems/wild monodromy re…

2019-03-29abs ↗pdf ↗

New model improves recommendation systems by analyzing user-item interactions.

problem Improving recommendation systems for better user-item interactions.
method Sliced Anti-symmetric Decomposition (SAD) model using tensor decomposition.
result SAD produces the most consistent personalized preferences compared to SOTA models.

Study automorphism groups' action on Jacobi diagrams, leading to new decompositions.

problem Understanding automorphism groups' actions on Jacobi diagrams.
method Analyzing the induced actions on graded vector spaces and constructing polynomial functors.
result Indecomposable decomposition of A2(n)A_2(n) and polynomial functor construction.

New matrix approximation method using RBF components for better memory efficiency.

problem Efficiently approximate any real matrix without being symmetric or positive definite.
method Formulate as an optimization problem with gradient descent methods.
result Significantly reduces memory usage for various matrix types.

We break down transformer embeddings into interpretable components revealing hidden geometric structures.

problem Understanding the hidden geometry and interpretability of transformer models.
method Decomposed transformer embeddings into position, context, and residual components.
result Pervasive mathematical structure in transformer embeddings, including position and context vectors.

This paper deals with some basic constructions of linear and multilinear algebra on finite-dimensional diffeological vector spaces. We consider the diffeological dual formally checking that the assignment to each space of its dual defines a covariant functor from the category of finite-dimensional diffeological vector …

2015-04-30abs ↗pdf ↗