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.
Generalizes Thurston's asymmetric metric to flat metrics.
Study of geometric analysis on asymmetric metric spaces, including heat flow and Sobolev spaces.
New metrics for Anosov representations defined from Thurston's asymmetric metrics.
Extends metric to Margulis spacetimes for convex properties.
We highlight several analogies between the Finsler (infinitesimal) properties of Teichmüller's metric and Thurston's asymmetric metric on Teichmüller space. Thurston defined his asymmetric metric in analogy with Teichmüllers' metric, as a solution to an extremal problem, which consists, in the case of the asymmetric me…
This paper studies gradient flows in asymmetric metric spaces and proves existence results.
We quantitatively relate the Patterson-Sullivant currents and generic stretching factors for free group automorphisms to the asymmetric Lipschitz metric on Outer space and to Guirardel's intersection number.
Paper proves rigidity theorems for geodesically reversible Finsler metrics.
New asymmetric metric on Teichmüller space for surfaces.
New separation concepts for Anosov representations help bound Thurston asymmetric metric.
In the asymmetric setting, Hilbert's fourth problem asks to construct and study all (non-reversible) projective Finsler metrics: Finsler metrics defined on open, convex subsets of real projective -space for which geodesics lie on projective lines. While asymmetric norms and Funk metrics provide many examples of esse…
We initiate the rigorous study of classification in quasi-metric spaces. These are point sets endowed with a distance function that is non-negative and also satisfies the triangle inequality, but is asymmetric. We develop and refine a learning algorithm for quasi-metrics based on sample compression and nearest neighbor…
The paper tackles multi-player information asymmetry bandits in metric spaces.
In this work we describe horofunction compactifications of metric spaces and finite dimensional real vector spaces through asymmetric metrics and asymmetric polyhedral norms by means of nonstandard methods, that is, ultrapowers of the spaces at hand. The polyhedral compactifications of the vector spaces carry the struc…
New metrics derived from Hölder distortion on Hitchin components.
New metric on geodesic currents connects different surface genera.
The paper describes geometric properties of Teichmüller space metrics.
A new method uses asymmetric Shapley values to assess gene importance in clinical prediction models.
The paper studies curves in Finsler-like spaces and their properties.
We study the action of the elements of the mapping class group of a surface of finite type on the Teichmüller space of that surface equipped with Thurston's asymmetric metric. We classify such actions as elliptic, parabolic, hyperbolic and pseudo-hyperbolic, depending on whether the translation distance of such an elem…
New framework improves differential privacy for asymmetric datasets.
Online Active Learning (OAL) aims to manage unlabeled datastream by selectively querying the label of data. OAL is applicable to many real-world problems, such as anomaly detection in health-care and finance. In these problems, there are two key challenges: the query budget is often limited; the ratio between classes i…
Study on earthquake metric on Teichmüller space, proving properties and new completions.
On a convex body in a Euclidean space, we introduce a new variational formulation for its Funk metric, a Finsler metric compatible with the tautological Finsler structure of the convex body. We generalize the metric on Teichmuller spaces with the Weil-Petersson distance function. A set of similarities the resulting met…
The arc metric is an asymmetric metric on the Teichm{ü}ller space T(S) of a surface S with nonempty boundary. In this paper we study the relation between Thurston's compactification and the horofunction compactification of T(S) endowed with the arc metric. We prove that there is a natural homeomorphism between the two …
Random walks on free groups reveal asymmetric expansion factors.
The aim of this paper is to relate Thurston's metric on Teichmüller space to several ideas initiated by T. Sorvali on isomorphisms between Fuchsian groups. In particular, this will give a new formula for Thurston's asymmetric metric for surfaces with punctures. We also update some results of Sorvali on boundary isomorp…
The paper defines a metric on Euclidean triangles and polygons, proving properties and completeness.
The Teichmüller space of a surface is equipped with Thurston's asymmetric metric. Stretch lines are oriented geodesics for this metric on . We give the asymptotic behavior of the lengths of the measured geodesic laminations as one follows a stretch line in the positive direction.
New friction model for geometric locomotion systems.
Gradient descent solves asymmetric low-rank matrix sensing without balancing.
New insights into currents of Hitchin representations with combinatorial restrictions.
We show that the length function of a measured geodesic lamination is convex in Thurston's shear coordinates over Teichmüller space and strictly convex for generic laminations. We give some consequences of this result in the context of Thurston's asymmetric metric on Teichmüller space.
This study examines asymmetric cross-correlations in cryptocurrency markets using fractal analysis.
We introduce an asymmetric distance function, which we call the `left Hausdorff distance function', on the space of geodesic laminations on a closed hyperbolic surface of genus at least 2. This distance is an asymmetric version of the Hausdorff distance between compact subsets of a metric space. We prove a rigidity res…
Theoretical justification for asymmetric actor-critic algorithms in reinforcement learning.
Characterizes isometries between non-reversible Finsler manifolds.
This work presents deep asymmetric networks with a set of node-wise variant activation functions. The nodes' sensitivities are affected by activation function selections such that the nodes with smaller indices become increasingly more sensitive. As a result, features learned by the nodes are sorted by the node indices…
We consider the problem of designing locality sensitive hashes (LSH) for inner product similarity, and of the power of asymmetric hashes in this context. Shrivastava and Li argue that there is no symmetric LSH for the problem and propose an asymmetric LSH based on different mappings for query and database points. Howev…
New asymmetric kernel methods improve feature learning.
The article confirms two quasi-alternating surgeries for 9 asymmetric L-space knots.
The paper improves asymmetric causality tests by addressing inefficiencies and statistical significance issues.
We propose Deep Asymmetric Multitask Feature Learning (Deep-AMTFL) which can learn deep representations shared across multiple tasks while effectively preventing negative transfer that may happen in the feature sharing process. Specifically, we introduce an asymmetric autoencoder term that allows reliable predictors fo…
In this paper we show how the study of asymmetric R&D alliances, that are those between young and small firms and large and MNEs firms for knowledge exploration and/or exploitation, requires the adoption of a coopetitive framework which consider both collaboration and competition. We draw upon the literature on asymmet…
Bayesian VI copula models capture asymmetric intraday equity dependence.
Extends multidimensional scaling to analyze three-way asymmetric proximities.
Study improves confidence measures in medical imaging pipelines by addressing bias.
In recent years, correntropy has been seccessfully applied to robust adaptive filtering to eliminate adverse effects of impulsive noises or outliers. Correntropy is generally defined as the expectation of a Gaussian kernel between two random variables. This definition is reasonable when the error between the two random…