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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.

168,695 papers · 148 categories

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102204306408 · Jun 202019922001200920172026
48 results for proper development

The paper studies ff-biharmonic maps and submersions in space forms.

problem Characterizing ff-biharmonic maps and submersions in space forms.
method Analyzing ff-biharmonic curves, developing classifications, and using integrability data.
result Proper ff-biharmonic developable surfaces exist only in the case of cylinders.

The paper explores proper actions and their relation to representation theory, with new quantitative methods.

problem Understanding proper actions and their connection to representation theory.
method Geometric criteria, sharpness measure, and dynamical volume estimates.
result New quantitative methods have established temperedness criteria for unitary representations.

Paper develops proper, lower-bounded losses for weakly supervised classification.

problem Weakly supervised classification with corrupted labels.
method Representation theorem for proper losses, derived condition for lower-boundedness, generalized logit squeezing.
result Proper and lower-bounded losses for weak-label learning.

In this paper, we apply the method developed in [Ti97] and [TZ00] to proving the properness of log FF-functional on any conic Kähler-Einstein manifolds. As an application, we give an alternative proof for the openness of the continuity method through conic Kähler-Einstein metrics.

2015-04-13abs ↗pdf ↗

We introduce a Hopf algebroid associated to a proper Lie group action on a smooth manifold. We prove that the cyclic cohomology of this Hopf algebroid is equal to the de Rham cohomology of invariant differential forms. When the action is cocompact, we develop a generalized Hodge theory for the de Rham cohomology of inv…

2010-02-23abs ↗pdf ↗

Unique domain found in Einstein universe, simplifying manifold classification.

problem Classifying closed conformally flat manifolds with proper development.
method Identifying and analyzing almost-homogeneous domains in the Einstein universe.
result Found a unique domain (diamond) in the Einstein universe that simplifies manifold classification.

Complex-valued signals are used in the modeling of many systems in engineering and science, hence being of fundamental interest. Often, random complex-valued signals are considered to be proper. A proper complex random variable or process is uncorrelated with its complex conjugate. This assumption is a good model of th…

2015-02-17abs ↗pdf ↗

The article reviews scoring rules for estimating and evaluating forecasts.

problem Evaluating probabilistic forecasts and estimating probability distributions.
method Mathematical foundations and characterization of scoring rules.
result Important families of scoring rules and their applications in statistics and machine learning.

The paper shows how contracting elements in groups lead to large quotients with specific growth rates.

problem Understanding the growth rates of group actions with contracting elements.
method Using extension lemma, rotating families theory, and quasi-tree construction.
result There exist sequences of quotient groups with growth rates approaching the original group's growth rate.

In this article we extend the classical definitions of equivariant cohomotopy theory to the setting of proper actions of Lie groups. We combine methods originally developed in the analysis of nonlinear differential equations, mainly in connection with Leray-Schauder theory, and on the other hand from developments of eq…

2013-02-07abs ↗pdf ↗

New concept of proper-calibeating extends classic calibrated forecasts to proper scoring rules.

problem Defining and extending calibrated forecasts to proper scoring rules.
method Extending the concepts of calibrated and calibeating forecasts to proper scoring rules and proving their properties.
result Proper-calibration always implies calibration, but proper-calibeating does not necessarily imply calibeating.

We develop a coarse notion of bundle and use it to understand the coarse geometry of group extensions and, more generally, groups acting on proper metric spaces. The results are particularly sharp for groups acting on (locally finite) trees with Abelian stabilizers, which we are able to classify completely.

2010-06-17abs ↗pdf ↗

The paper develops theory for holomorphic null curves in SL2(C).

problem Developing theory for holomorphic null curves in SL2(C).
method Establish Runge, Mergelyan, Mittag-Leffler, and Carleman type theorems for holomorphic null immersions.
result Proves every open Riemann surface admits a proper holomorphic null embedding into SL2(C).

We establish the Thom isomorphism in twisted K-theory for any real vector bundle and develop the push-forward map in twisted K-theory for any differentiable proper map f:XYf: X\to Y (not necessarily K-oriented). The push-forward map generalizes the push-forward map in ordinary K-theory for any KK-oriented differentiable…

2005-07-21abs ↗pdf ↗

The paper decomposes probabilistic scores into reliability, uncertainty, and information loss.

problem Understanding the reliability and uncertainty of probabilistic predictions.
method Developed decomposition identities for proper losses, quantifying reliability, residual uncertainty, and information gain.
result A three-term identity for classification scores, revealing miscalibration, grouping term, and feature-level uncertainty.

This study considers that the collective route choices of travelers en route represent a resolution of their competition on network routes. Well understanding this competition and coordinating their route choices help mitigate urban traffic congestion. Even though existing studies have developed such mechanisms (e.g., …

2019-11-12abs ↗pdf ↗

This is a concise introduction to the theory of Lie groupoids, with emphasis in their role as models for stacks. After some preliminaries, we review the foundations on Lie groupoids, and we carefully study equivalences and proper groupoids. Differentiable stacks are geometric objects which have manifolds and orbifolds …

2012-12-30abs ↗pdf ↗

We show that immersed minimal surfaces of R3\mathbb{R}^{3} with bounded curvature and proper self intersections are proper. We also show that the restriction of the immersing map to a wide component is always proper. When the immersing map is injective the whole surface is a wide component. Prior to these results it wa…

2002-05-28abs ↗pdf ↗

In this paper we extend recent breakthrough of Chen-Cheng \cite{CC1, CC2, CC3} on existence of constant scalar Kähler metric on a compact Kähler manifold to Calabi's extremal metric. Our argument follows \cite{CC3} and there are no new a prior estimates needed, but rather there are necessary modifications adapted to th…

2018-01-23abs ↗pdf ↗

Classifies non-linear Fredholm maps linking to stable homotopy groups of spheres.

problem Classifying non-linear proper Fredholm maps between Hilbert spaces.
method Using stable homotopy groups of spheres to classify maps up to proper homotopy.
result Determines the non-trivial kernel of the map from stable homotopy groups to non-linear proper Fredholm maps.

A novel framework quantifies uncertainty using proper scores for various tasks.

problem Uncertainty quantification in machine learning for reliable applications.
method Proposes a general framework based on proper scores for epistemic, aleatoric uncertainty, and model calibration.
result Achieves state-of-the-art uncertainty estimation for large language models and generative models.

First example of open manifold with positive Ricci curvature and non-proper Busemann function.

problem Counterexample to Busemann function properness in open manifolds with nonnegative Ricci curvature.
method Provided an open manifold with positive Ricci curvature and non-proper Busemann function.
result First example of open manifold with positive Ricci curvature and non-proper Busemann function.

Develops moduli theory for Calabi-Yau pairs, constructing a projective space.

problem Constructing a moduli space for Calabi-Yau pairs at the Calabi-Yau wall.
method Develops moduli theory, proving S-completeness and ΘΘ-reductivity, constructing projective moduli space.
result Constructs a projective moduli space for degenerate P2\mathbb{P}^2 pairs.

First proper learning algorithm for Gaussian halfspaces with matching sample and computational complexity.

problem Agnostically learning halfspaces under Gaussian distribution.
method First proper learning algorithm with matching sample and computational complexity.
result First proper learning algorithm for agnostically learning halfspaces under Gaussian distribution with matching sample and computational complexity.

New method constructs proper affine actions of groups in higher dimensions.

problem Finding proper affine actions of discrete groups in higher-dimensional spaces.
method Higher strip deformations and Margulis invariant for properness.
result Affine actions of convex cocompact groups and virtually free groups are constructed properly.

Estimates proper calibration errors and refinement terms in probabilistic predictions.

problem Lack of a general estimator for proper calibration errors and refinement terms with known statistical properties.
method Proposes a method for consistent, asymptotically unbiased estimation of proper calibration errors and refinement terms.
result Proves the relation between refinement and f-divergences, implying information monotonicity in neural networks.

Recently, based on the idea of randomizing space theory, random convex analysis has been being developed in order to deal with the corresponding problems in random environments such as analysis of conditional convex risk measures and the related variational problems and optimization problems. Random convex analysis is …

2016-03-23abs ↗pdf ↗

Sharpness of actions on reductive homogeneous spaces proven for various groups.

problem Proving proper and cocompact actions on reductive homogeneous spaces.
method Using quasi-isometric embedding and Anosov representations.
result Characterization and proof of non-compactness for certain homogeneous spaces.

In this paper we prove that every proper Lie groupoid admits a desingularization to a regular proper Lie groupoid. When equipped with a Riemannian metric, we show that it admits a desingularization to a regular Riemannian proper Lie groupoid, arbitrarily close to the original one in the Gromov-Hausdorff distance betwee…

2017-06-23abs ↗pdf ↗

Study proper actions of Lie groups on symmetric spaces, finding rigidity results and Hurwitz-Radon numbers.

problem Proper actions of non-compact semisimple Lie groups on pseudo-Riemannian symmetric spaces.
method Analysis of symmetric spaces and rigidity results.
result Any connected non-compact semisimple Lie group acting properly on these spaces must be globally isomorphic to Spin(n,1)Spin(n,1) up to compact factors.

Develops Palatini formalism in generalized geometry for string theory.

problem Formulating Palatini variation in generalized geometry.
method Palatini formalism within generalized Riemannian geometry of Courant algebroids.
result Natural emergence of generalized Levi-Civita connection and string effective actions.

Paper tackles infinite-dimensional optimization and Bayesian learning for stochastic differential equations.

problem Learning the drift function of stochastic differential equations with uncertainty quantification.
method Combines infinite-dimensional optimization results with Bayesian hierarchical framework, incorporating shrinkage priors for sparse learning.
result Systematic approach for accurate learning of stochastic differential equations with uncertainty quantification.

New method improves neural network interpretability against adversarial attacks.

problem Adversarial attacks can hide from neural network interpretability methods.
method Develops an interpretability-aware defensive scheme promoting robust interpretation.
result Achieves both robust classification and robust interpretation.

Study on proper learning under relaxed worst-case robust loss for VC classes.

problem Proper adversarially robust PAC learning under relaxed worst-case robust loss.
method Introduced a family of robust loss relaxations and showed their effectiveness for proper learnability.
result VC classes are properly PAC learnable with sample complexity close to standard PAC learning setup.