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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.

168,742 papers · 148 categories

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76151227302 · May 202619922001200920172026
48 results for nonsymmetric derivations

New Einstein solvmanifolds constructed without using nilsolitons.

problem Constructing Einstein solvmanifolds not based on nilsolitons.
method Using nonsymmetric derivations and a computer algorithm to classify and find solutions up to dimension 9.
result Einstein solvmanifolds of dimensions ≤ 5 are not isometric to standard extensions of nilsolitons.

We characterize lower bounds for the Bakry-Emery Ricci tensor of nonsymmetric diffusion operators by convexity of entropy on the L2L^2-Wasserstein space, and define a curvature-dimension condition for general metric measure spaces together with a square integrable 11-form in the sense of \cite{giglinonsmooth}. This ex…

2016-06-22abs ↗pdf ↗

We formulate an approach to the geometry of Riemann-Cartan spaces provided with nonholonomic distributions defined by generic off-diagonal and nonsymmetric metrics inducing effective nonlinear and affine connections. Such geometries can be modelled by moving nonholonomic frames on (pseudo) Riemannian manifolds and desc…

2008-06-24abs ↗pdf ↗

New algorithm scales NDPP learning and inference to large item collections.

problem Memory and runtime limitations in existing NDPP learning and inference algorithms.
method Introduced a new NDPP kernel decomposition for learning and a linear-complexity MAP inference algorithm.
result Our algorithms scale linearly in MM, matching prior work's predictive performance.

The paper presents the Einstein connection for nonsymmetric pseudo-Riemannian manifolds with specific torsion conditions.

problem Tackles the Einstein connection in nonsymmetric pseudo-Riemannian manifolds with non-degenerate skew-symmetric tensor.
method Explicitly presents the Einstein connection for nonsymmetric pseudo-Riemannian manifolds with f2f^2-torsion condition.
result Reduces to M.Prvanović's solution in the almost Hermitian case.

The paper presents the Einstein connection for nonsymmetric pseudo-Riemannian manifolds.

problem The challenge is to define the Einstein connection for nonsymmetric pseudo-Riemannian manifolds.
method The approach involves using a weak almost contact structure and a linear connection with torsion.
result Explicit formulas for the Einstein connection are provided.

Determinantal point processes (DPPs) have attracted substantial attention as an elegant probabilistic model that captures the balance between quality and diversity within sets. DPPs are conventionally parameterized by a positive semi-definite kernel matrix, and this symmetric kernel encodes only repulsive interactions …

2019-05-30abs ↗pdf ↗

Symmetric nonnegative matrix factorization (NMF), a special but important class of the general NMF, is demonstrated to be useful for data analysis and in particular for various clustering tasks. Unfortunately, designing fast algorithms for Symmetric NMF is not as easy as for the nonsymmetric counterpart, the latter adm…

2018-11-14abs ↗pdf ↗

This work tackles scalable sampling for nonsymmetric DPPs.

problem Scalability issue in existing DPP sampling algorithms for nonsymmetric DPPs.
method Developed a linear-time algorithm for kernels with low-rank structure and a sublinear-time rejection sampling algorithm.
result Bounded rejection rate for kernels with structural constraints.

We classify noncompact homogeneous spaces which are Einstein and asymptotically harmonic. This completes the classification of Riemannian harmonic spaces in the homogeneous case: Any simply connected homogeneous harmonic space is flat, or rank-one symmetric, or a nonsymmetric Damek-Ricci space. Independently, Y. Nikola…

2004-09-20abs ↗pdf ↗

We show the existence of nonsymmetric homogeneous spin Riemannian manifolds whose Dirac operator is like that on a Riemannian symmetric spin space. Such manifolds are exactly the homogeneous spin Riemannian manifolds (M,g)(M,g) which are traceless cyclic with respect to some quotient expression M=G/KM=G/K and reductive decom…

2015-04-22abs ↗pdf ↗

We study a natural Lie algebra structure on the free vector space generated by all rooted planar trees as the associated Lie algebra of the nonsymmetric operad (non-ΣΣ operad, preoperad) of rooted planar trees. We determine whether the Lie algebra and some related Lie algebras are finitely generated or not, and prove …

2011-05-24abs ↗pdf ↗

A Riemannian manifold is called harmonic if its volume density function expressed in polar coordinates centered at any point is radial. Flat and rank-one symmetric spaces are harmonic. The converse (the Lichnerowicz Conjecture) is true for manifolds of nonnegative scalar curvature and for some other classes of manifold…

2004-07-02abs ↗pdf ↗

Our aim is to introduce and advocate non-ΣΣ (non-symmetric) modular operads. While ordinary modular operads were inspired by the structure of the moduli space of stable complex curves, non-ΣΣ modular operads model surfaces with open strings outputs. An immediate application of our theory is a short proof that the mod…

2014-10-13abs ↗pdf ↗

In this work we study riemannian metrics on flag manifolds adapted to the symmetries of these homogeneous nonsymmetric spaces. We first introduce the notion of riemannian ΓΓ-symmetric space when ΓΓ is a general abelian finite group, the symmetric case corresponding to Γ=Z2Γ=\Z_2. We describe and study all the riemannia…

2006-09-28abs ↗pdf ↗

Ensembles improve classifier performance by reducing bias, not variance.

problem Improving classifier performance through ensemble methods.
method Extended bias-variance decomposition for classification tasks, introducing dual reparameterization.
result Ensembling reduces bias in classifiers, contrary to the traditional view.

Computing the partition function ZZ of a discrete graphical model is a fundamental inference challenge. Since this is computationally intractable, variational approximations are often used in practice. Recently, so-called gauge transformations were used to improve variational lower bounds on ZZ. In this paper, we pro…

2018-01-05abs ↗pdf ↗

The study classifies homogeneous Sasaki manifolds over quaternionic Kähler spaces.

problem Classifying homogeneous Sasaki manifolds over quaternionic Kähler spaces.
method Locally defined Riemannian submersions and homogeneous space constructions.
result Complete classification of homogeneous Sasaki manifolds in the non-degenerate case.

Multiresolution Matrix Factorization (MMF) was recently introduced as an alternative to the dominant low-rank paradigm in order to capture structure in matrices at multiple different scales. Using ideas from multiresolution analysis (MRA), MMF teased out hierarchical structure in symmetric matrices by constructing a se…

2019-10-10abs ↗pdf ↗

New algorithm approximates maximum of certain distributions on subsets.

problem Finding maximum of distributions on subsets.
method Connection between sampling and optimization via exchange inequalities and local random walks.
result Simple nearly-optimal approximation algorithm for MAP inference.

We consider a nonlinear extension of the generalized network flow model, with the flow leaving an arc being an increasing concave function of the flow entering it, as proposed by Truemper and Shigeno. We give a polynomial time combinatorial algorithm for solving corresponding flow maximization problems, finding an epsi…

2011-09-18abs ↗pdf ↗

We study direct limits (G,K)=lim(Gn,Kn)(G,K) = \varinjlim (G_n,K_n) of compact Gelfand pairs. First, we develop a criterion for a direct limit representation to be a multiplicity--free discrete direct sum of irreducible representations. Then we look at direct limits G/K=limGn/KnG/K = \varinjlim G_n/K_n of compact riemannian symmetric spaces, …

2008-01-25abs ↗pdf ↗

A new method estimates parameters in heavy-tailed corrupted regression with unknown covariance and heterogeneous noise.

problem Estimating parameters in regression with heavy-tailed errors and unknown covariance.
method Near-optimal computationally tractable estimator based on power method and Multiplicative Weight Update algorithm.
result The estimator achieves the optimal statistical rate and breakdown-point under near-optimal sample size.

Researchers found the Wigner derivative and its inverse are equal for spherical tetrahedra.

problem Computing the relationship between dihedral angles and edge lengths in tetrahedra.
method Computed the Wigner derivative and its inverse for spherical tetrahedra.
result The Wigner derivative and its inverse are equal for spherical tetrahedra.

The paper shows objective derivatives are covariant derivatives on Riemannian metrics.

problem The definition and interpretation of objective derivatives in continuum mechanics.
method Demonstrates that objective derivatives correspond to covariant derivatives on the manifold of Riemannian metrics.
result Objective derivatives are unified as covariant derivatives on the manifold of Riemannian metrics.

Schwarzian derivative connects to Euler-Lagrange equations in variational calculus.

problem Understanding the relationship between the Schwarzian derivative and variational equations.
method Analyzing the Schwarzian derivative as a first integral and Euler-Lagrange operator for specific variations.
result The Schwarzian derivative is both a first integral and the Euler-Lagrange operator for a certain class of variations.

Paper develops formulas for shape derivatives in wave scattering.

problem Computing high order shape derivatives for wave scattering is challenging.
method Introduces elegant recurrence formulas using differential forms and Lie derivatives.
result Unified framework for computing high order shape perturbations in scattering problems.

New derivations on diffeological spaces are not smooth, expanding tangent space definitions.

problem Lack of smoothness in derivations on diffeological spaces.
method Examined derivations satisfying the Leibniz rule but not smooth with respect to given diffeology.
result Tangent space defined via all derivations is larger than one defined using only smooth derivations.