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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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48 results for Hessian geometry

Study the Hessian geometry of an ideal gas in a centrifuge.

problem Understanding the Hessian geometry of an ideal gas in a centrifuge.
method Investigate the Hessian geometry associated with an ideal gas in a spherical centrifuge, using the action of the Euclidean rotation group.
result The Hessian geometry of a spherical rigid body is isometric to a hyperbolic space in the high angular velocity limit.

The target space geometry of abelian vector multiplets in N=2{\cal N}= 2 theories in four and five space-time dimensions is called special geometry. It can be elegantly formulated in terms of Hessian geometry. In this review, we introduce Hessian geometry, focussing on aspects that are relevant for the special geometrie…

2019-09-13abs ↗pdf ↗

Curved Frobenius manifolds link to Hessian metrics in geometry.

problem Understanding curved Frobenius manifolds and their relation to Hessian metrics.
method Analyzing the relationship between curved Frobenius structures and Hessian metrics on spaces with non-vanishing curvature.
result Consistent curved Frobenius structures on constant curvature spaces are linked to Hessian metrics.

The Hessian geometry is the real analogue of the Kähler one. Sasakian geometry is an odd-dimensional counterpart of the Kähler geometry. In the paper, we study the connection between projective Hessian and Sasakian manifolds analogous to the one between Hessian and Kähler manifolds. In particular, we construct a Sasaki…

2018-03-07abs ↗pdf ↗

A family of probability distributions parametrized by an open domain ΛΛ in RnR^n defines the Fisher information matrix on this domain which is positive semi-definite. In information geometry the standard assumption has been that the Fisher information matrix tensor is positive definite defining in this way a Riemannia…

2015-03-29abs ↗pdf ↗

The paper introduces statistical and geometric structures on anti-commutable pre-Leibniz algebroids.

problem Generalizing differential geometric structures to algebroids.
method Introducing statistical, conjugate connection, and Hessian structures on anti-commutable pre-Leibniz algebroids.
result Statistical and conjugate connection structures are equivalent for admissible connections.

Optimizes quadratic bandits with tight Hessian-dependent sample complexity bounds.

problem Understanding optimal sample complexity for quadratic functions.
method Introduces energy allocation and optimal energy spectrum to prove tight lower bounds. Solves for Hessian-independent optimal algorithm.
result Proves optimal Hessian-dependent sample complexities and existence of a universally optimal algorithm.

Study of contravariant pseudo-Hessian manifolds and their Poisson structures.

problem Understanding properties of contravariant pseudo-Hessian manifolds.
method Investigation of flat connections and symmetric bivector fields satisfying a contravariant Codazzi equation.
result Association of a Poisson tensor to contravariant pseudo-Hessian manifolds.

The paper explores the geometric structure of cost functions in multiple dimensions.

problem Understanding the geometric properties of cost functions in multidimensional settings.
method Analyzes the Hessian metric and geodesics in logarithmic and original coordinates.
result The geometry is one-dimensional in logarithmic coordinates but effectively (n1)(n-1)-dimensional in original coordinates.

New Hessian estimators for Riemannian manifolds with reduced bias.

problem Estimating Hessians on Riemannian manifolds with reduced bias and computational efficiency.
method Introducing new stochastic zeroth-order Hessian estimators using O(1)O(1) function evaluations.
result Achieved a bias bound of order O(γδ2)O(γδ^2) for analytic real-valued functions.

Study proves estimate for Hessian quotient equations on 2D Riemannian manifolds.

problem Problems posed by Delanoë and Urbas related to Hessian quotient equations.
method Maximum principle argument and new test function introduced to prove estimate.
result Unobstructed second order a priori estimate for real Hessian quotient equation in 2D.

The paper introduces a new differential-geometric system which originates from the theory of mm-Hessian operators. The core of this system is a new notion of invariant differentiation on multidimensional surfaces. This novelty gives rise to the following absolute geometric invariants: invariant derivatives of the surf…

2019-04-08abs ↗pdf ↗

Paper analyzes latent space geometry in generative models using Fisher information.

problem Understanding the structure of latent spaces in generative models.
method Reconstructs Fisher information metric from generated samples and posterior distribution.
result Reveals fractal structure and abrupt changes in Fisher metric at phase boundaries.

CWGD measures gradient diversity weighted by curvature, improving SGD convergence.

problem Gradient noise in high-curvature directions is underestimated by standard methods.
method CWGD weights gradient diversity by the inverse square root of the Hessian.
result CWGD-Cosine reduces optimization error by up to 20% compared to standard cosine annealing.

The paper proves properties of geometric flows on noncompact manifolds.

problem Existence criteria for geometric flows on noncompact affine Riemannian manifolds.
method Obtained existence criteria through a geometric flow on noncompact affine Riemannian manifolds.
result Complete noncompact Hessian manifolds with nonnegative Hessian sectional curvature and bounded geometry are diffeomorphic to \(\mathbb{R}^n\) if their tangent bundle has maximal volume growth.

Author presents the second variational formula for statistical biharmonic maps.

problem Developing a formula for statistical biharmonic maps.
method Introduced the second variational formula for the statistical bi-energy functional.
result The second variational formula can be represented using Hessian curvature in Hessian manifolds.

The paper defines Hesse solitons and explores their properties on Hessian manifolds.

problem Exploring self-similar solutions to the Hesse flow on Hessian manifolds.
method Defining Hesse solitons and analyzing their properties on Hessian manifolds.
result Compact proper Hesse solitons are expanding, and non-trivial compact gradient Hesse solitons are proper.

We study the Kepler metrics on Kepler manifolds from the point of view of Sasakian geometry and Hessian geometry. This establishes a link between the problem of classical gravity and the modern geometric methods in the study of AdS/CFT correspondence in string theory.

2017-08-18abs ↗pdf ↗

The paper studies the smoothness of critical points of variational integrals on Hessian spaces.

problem The study focuses on the regularity of critical points of variational integrals defined on Hessian spaces.
method The approach involves solving a fourth order nonlinear equation and analyzing the Hessian of the critical points.
result Smooth critical points with bounded Hessian are shown to be smooth provided their Hessian has small BMO.

The paper solves PDEs from matrices with orthogonal columns, linking them to Hessian metrics and symmetric spaces.

problem Solving third order PDEs for strictly convex smooth functions.
method Geometric methods using Hessian metrics and symmetric spaces.
result Explicit solutions and a family of non-generic solutions with applications in Poisson geometry and Kahler structures.

Develops new strategy for Hessian estimates in Lagrangian mean curvature equation.

problem Interior Hessian estimates for solutions with prescribed Lipschitz phases.
method Allard-type regularity theorem, geometric measure theory, geometry of Lagrangian graphs, De Giorgi-Nash-Moser iteration.
result Sharp interior Hessian estimates for solutions with critical and supercritical phases.

Study the geometry of a Lie group using Hessian and flat affine structures.

problem Understanding the geometry of a specific Lie group.
method Examined using bi-invariant Hessian metric and flat affine structure, focusing on curvatures, causal structure, and developed map.
result Determined curvatures, tidal force, and Jacobi vector fields of the Hessian metric.

The study explores generalized divergences and exponential families with a focus on sufficient conditions and laws of large numbers.

problem Generalization of Kullback-Leibler divergence and exponential families.
method Investigation of (h,τ)(h,τ)-divergence and (h,τ)(h,τ)-exponential families, definition of (h,τ)(h,τ)-dependence, proof of law of large numbers.
result Sufficient condition for (h,τ)(h,τ)-divergence to induce Hessian structure on (h,τ)(h,τ)-exponential family, proof of law of large numbers.

In this brief survey, we will remark the interaction among the Hessian tensor on a semi-Riemannian manifold and some of the several questions in Lorentzian (and also in semi-Riemannian) geometry where this 2-covariant tensor is involved. In particular, we deal with the characterization of Killing vector fields and the …

2006-07-05abs ↗pdf ↗

The paper finds convex hypersurfaces with specific curvature properties.

problem Finding convex hypersurfaces with prescribed Hessian curvatures and Gauss images.
method Used novel C2C^2 boundary estimates based on orthogonal invariance and infinitesimal rotations.
result Proved existence of strictly convex graphic hypersurfaces with prescribed kk-Hessian curvatures.

New method computes affine normal directions efficiently for sparse polynomials.

problem Computing affine normal directions is computationally expensive in high dimensions.
method Reduces third-order tensor contraction to matrix-free formulation using log-determinant gradient.
result Scalable implementations with near-linear scaling in dimension and sparsity.

The expression (-1/u) times the Hessian of u transforms as a symmetric (0,2) tensor under projective coordinate transformations, so long as u transforms as a section of a certain line bundle. On a locally projectively flat manifold M, the section u can be regarded as a metric potential analogous to the local potential …

2001-08-30abs ↗pdf ↗

Introduces a new geometric structure for statistical manifolds with degenerate metrics.

problem Degenerate metrics in statistical manifolds affect geometric structures and applications.
method Introduces quasi-Codazzi structure for degenerate metrics and coherent tangent bundles.
result Generalizes geometric structures and relations for statistical models with degenerate metrics.

New method proves asymptotic normality for matrix sensing problems.

problem Proving asymptotic normality for matrix sensing under general convex losses.
method Riemannian geometry to handle degeneracy of the Hessian due to rotational symmetry.
result Proves n(φ0φ)DN(0,(H)1)\sqrt{n}(φ^0-φ^*)\xrightarrow{D}N(0,(H^*)^{-1}) as non o\infty.

Noise injection regularizes Hessian, improving neural network training and generalization.

problem Regularizing over-parameterized neural networks with nonconvex and nonlinear geometry.
method Injecting isotropic Gaussian noise into weight matrices and designing a two-point estimate of the Hessian penalty.
result Effective regularization of Hessian improves generalization, achieving up to 2.4% test accuracy increase.

Study of manifolds with flat connections and diagonal metrics leading to vanishing Euler characteristic.

problem Understanding the geometry and topology of affine-orthogonal manifolds.
method Deformation of flat connections into Levi-Civita connections and analysis of Euler characteristic.
result Deformations force the Euler characteristic to vanish, supporting Chern's conjecture.