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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.

168,932 papers · 148 categories

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82164246328 · Jun 202019922001200920172026
48 results for metric context

The paper connects counterfactual fairness to robust prediction and group fairness using causal context.

problem The challenge of ensuring fairness in AI systems when counterfactuals cannot be directly observed.
method Using causal context to bridge counterfactual fairness, robust prediction, and group fairness.
result Counterfactual fairness is equivalent to group fairness metrics in specific contexts.

Spatially-aware metrics improve uncertainty evaluation in segmentation.

problem Uncertainty evaluation metrics treat voxels independently, ignoring spatial context.
method Proposed three spatially aware metrics incorporating structural and boundary information.
result Improved alignment with clinically important factors and better discrimination between uncertainty patterns.

The paper studies projectively equivalent para-Kaehler metrics in 4D.

problem Characterizing para-Kaehler metrics with specific properties.
method Developed c-projective geometry for para-Kaehler metrics, focusing on 4D case.
result Local description and characterization of 4D pc-projectively equivalent metrics, including Einstein type.

We study branched covering spaces in several contexts, proving that under suitable circumstances the cover satisfies the same upper curvature bounds as the base space. The first context is of a branched cover of an arbitrary metric space that satisfies Alexandrov's curvature condition CAT(k), over an arbitrary complete…

1999-05-26abs ↗pdf ↗

Algorithm learns similarities to optimize bandit decisions in unknown metric space.

problem Optimizing decisions in unknown metric space with nonparametric reward functions.
method Data-driven similarities for adaptive partitioning of context-arm space.
result Regret bounds highlight algorithm's dependence on reward functions' local geometry.

On connected manifolds of dimension higher than three, the non-existence of 132132 Chinea and González-Dávila types of almost contact metric structures is proved. This is a consequence of some interrelations among components of the intrinsic torsion of an almost contact metric structure. Such interrelations allow to des…

2018-02-22abs ↗pdf ↗

Suppose (X,ω)(X,ω) is a compact Kähler manifold. Following Mabuchi, the space of smooth Kähler potentials H\mathcal H can be endowed with a Riemannian structure, which induces an infinite dimensional path length metric space (H,d)(\mathcal H,d). We prove that the metric completion of (H,d)(\mathcal H,d) can be identified with …

2014-01-28abs ↗pdf ↗

This paper is a survey of some of the developments in coarse extrinsic geometry since its inception in the work of Gromov. Distortion, as measured by comparing the diameter of balls relative to different metrics, can be regarded as one of the simplist extrinsic notions. Results and examples concerning distorted subgrou…

1998-10-30abs ↗pdf ↗

We study harmonic almost contact structures in the context of contact metric manifolds, and an analysis is carried out when such a manifold fibres over an almost Hermitian manifold, as exemplified by the Boothby-Wang fibration. Two types of almost contact metric warped products are also studied, relating their harmonic…

2007-08-31abs ↗pdf ↗

In this note we use the Calabi ansatz, in the context of metrics with conical singularities along a divisor, to produce regular Calabi-Yau cones and Kähler-Einstein metrics of negative Ricci with a cuspidal point. As an application, we describe singularities and cuspidal ends of the completions of the complex hyperboli…

2018-04-18abs ↗pdf ↗

We provide an algebraic framework for quantization of Hermitian metrics that are solutions of the Hitchin equation for Higgs bundles over a projective manifold. Using Geometric Invariant Theory, we introduce a notion of balanced metrics in this context. We show that balanced metrics converge at the quantum limit toward…

2016-01-19abs ↗pdf ↗

Multi-task learning (MTL) improves prediction performance in different contexts by learning models jointly on multiple different, but related tasks. Network data, which are a priori data with a rich relational structure, provide an important context for applying MTL. In particular, the explicit relational structure imp…

2014-11-10abs ↗pdf ↗

ContextFlow++ improves generative models by conditioning on mixed-variable contexts.

problem Lack of effective methods for context conditioning in flow-based generative models.
method Proposes ContextFlow++ with additive conditioning and mixed-variable architecture.
result ContextFlow++ achieves higher performance metrics and faster training.

We reformulate the compatibility condition between a generalized metric and a small (non-maximal rank) Dirac structure in an exact Courant algebroid found in the context of the gauging of strings and formulated by means of two connections in purely Dirac-geometric terms. The resulting notion, a transverse generalized m…

2019-01-25abs ↗pdf ↗

This paper introduces C-DSL to improve data mining outcomes by considering context.

problem Data collection ambiguities, data imbalance, hidden biases, lack of domain info, and data incompleteness.
method Developed Context-Driven Data Science Lifecycle (C-DSL) to address data quality issues.
result Tangible improvements to data mining outcomes were achieved through C-DSL.

In the algebraic context, we show that null Osserman, spacelike Osserman, and timelike Osserman are equivalent conditions for a model of signature (2,2). We also classify the null Jordan Osserman models of signature (2,2). In the geometric context, we show that a pseudo-Riemannian manifold of signature (2,2) is null Jo…

2008-04-02abs ↗pdf ↗

Proposes a method to select fair performance metrics through metric elicitation.

problem Choosing fair performance metrics in multiclass classification with multiple sensitive groups.
method Metric elicitation strategy that requires only relative preference feedback and is robust to noise.
result Elicits group-fair performance metrics for multiclass classification problems.

Generalized Kahler geometry is the natural analogue of Kahler geometry, in the context of generalized complex geometry. Just as we may require a complex structure to be compatible with a Riemannian metric in a way which gives rise to a symplectic form, we may require a generalized complex structure to be compatible wit…

2010-07-20abs ↗pdf ↗

We prove an optimal systolic inequality for CAT(0) metrics on a genus~2 surface. We use a Voronoi cell technique, introduced by C.~Bavard in the hyperbolic context. The equality is saturated by a flat singular metric in the conformal class defined by the smooth completion of the curve y^2=x^5-x. Thus, among all CAT(0) …

2005-01-02abs ↗pdf ↗

The paper developes a geometrization of a Kronecker hh-regular vertical fundamental metrical d-tensor G(i)(j)(α)(β)G^{(α)(β)}_{(i)(j)} on the jet fibre bundle of order one J1(T,M)J^1(T,M). This geometrization gives a mathematical model for both gravitational and electromagnetic field theory, in a general setting. In this context, the…

2000-11-01abs ↗pdf ↗

Study compares metrics from negative curvature and quasi-Fuchsian representations.

problem Comparing metrics on surface groups from negative curvature and quasi-Fuchsian representations.
method Examines Teichmüller space as the intersection of two metric families.
result Teichmüller space is the only common part of the two metric families.

We study adaptive data-dependent dimensionality reduction in the context of supervised learning in general metric spaces. Our main statistical contribution is a generalization bound for Lipschitz functions in metric spaces that are doubling, or nearly doubling. On the algorithmic front, we describe an analogue of PCA f…

2013-02-12abs ↗pdf ↗

New metric and method for sEMG-based gesture recognition under domain shifts.

problem Measuring and adapting to domain divergence in sEMG-based gesture recognition.
method Probability distribution-based metric, 2-stage autoregressive RNN architecture.
result Improved autoregressive, RNN-based architecture enhances performance.

We investigate the class of geodesic metric discs satisfying a uniform quadratic isoperimetric inequality and uniform bounds on the length of the boundary circle. We show that the closure of this class as a subset of Gromov-Hausdorff space is intimately related to the class of geodesic metric disc retracts satisfying c…

2019-04-29abs ↗pdf ↗

The paper introduces contexture theory to characterize representation learning from contexts.

problem Lack of systematic characterization of representation learning methods.
method Characterizes representation learning as learning from the association between input and context variable.
result Contexture theory shows that representations can be approximated by top singular functions of the context.

We present the linearized metrizability problem in the context of parabolic geometries and subriemannian geometry, generalizing the metrizability problem in projective geometry studied by R. Liouville in 1889. We give a general method for linearizability and a classification of all cases with irreducible defining distr…

2018-03-28abs ↗pdf ↗

In the context of Thurstons geometrisation program we address the question which compact aspherical 3-manifolds admit Riemannian metrics of nonpositive curvature. We show that non-geometric Haken manifolds generically, but not always, admit such metrics. More precisely, we prove that a Haken manifold with, possibly emp…

1994-10-04abs ↗pdf ↗

AI benchmarks evaluate football team performance using generative models.

problem Evaluating human performance in complex interactive tasks is error-prone and unreliable.
method Trained Conditional VRNN Model on player and ball tracking data to imitate and predict team interactions.
result Trained model as a useful benchmark for evaluating team performance in football.

The paper explores how magnetic systems' spectra can identify metrics and 1-forms.

problem Can the marked magnetic action spectrum of magnetic systems with Anosov flow determine the metric and 1-form?
method The paper addresses this question in two settings: locally for systems with close metrics and 1-forms, and for metrics in the same conformal class.
result The paper answers the question affirmatively in both settings.