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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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15 results for pseudodistance

The paper revisits Markowitz's pseudodistance on pseudo-Riemannian manifolds.

problem Characterizing and classifying pseudo-Riemannian manifolds using Markowitz's pseudodistance.
method Review and extension of Markowitz's construction of pseudodistance on pseudo-Riemannian manifolds, with examples and classifications.
result Classification of quasi-homogeneous domains in the Einstein-de Sitter space.

We clarify the relationship between the null geodesic completeness of an Einstein Lorentz manifold and its conformal Kobayashi pseudodistance. We show that an Einstein manifold has at least one incomplete null geodesic if its pseudodistancfe is nontrivial. If its pseudodistance is nondegenerate, all of its null geodesi…

2011-08-09abs ↗pdf ↗

In this paper we define Kobayashi-Royden pseudonorm for almost complex manifolds. Its basic properties known from the complex analysis are preserved in the nonintegrable case as well. We prove that the pseudodistance induced by this pseudonorm coincides with the Kobayashi pseudodistance defined for the almost complex c…

1997-08-25abs ↗pdf ↗

The paper establishes Schwarz type lemmas for holomorphic maps between pseudo-Hermitian and Hermitian manifolds.

problem Analyzing holomorphic maps between pseudo-Hermitian and Hermitian manifolds.
method Using Bochner formulas and comparison theorems.
result Established Schwarz type lemmas for holomorphic maps.

Let SS be a closed and oriented surface of genus gg at least 22. In this (mostly expository) article, the object of study is the space P(S)\mathcal{P}(S) of marked isomorphism classes of projective structures on SS. We show that P(S)\mathcal{P}(S), endowed with the canonical complex structure, carries exotic hermitian …

2018-12-03abs ↗pdf ↗

We provide two main contributions in PAC-Bayesian theory for domain adaptation where the objective is to learn, from a source distribution, a well-performing majority vote on a different, but related, target distribution. Firstly, we propose an improvement of the previous approach we proposed in Germain et al. (2013), …

2017-07-17abs ↗pdf ↗