arXiv research

Empirical study on hyperparameters affecting RL generalization.

Paper reduces sample complexity for bilinear systems identification to nearly constant.

Proposes a framework to quantify uncertainty in multi-step decision-making by LLMs.

Extends RL to random stopping times, improving optimization.

OSGM uses online learning to adapt stepsize for faster convergence.

Model trains agents to optimize saving and investment strategies for diverse retirement needs.

Unified framework for multi-view diffusion geometries using intertwined diffusion trajectories.

DSPI connects natural policy gradient to policy iteration, proving global convergence.

Revisiting Trade-sign Long-memory and Square-root Law price impact

Method learns dynamics from noisy partial observations.

Develops anytime-valid stopping rules for SGD based on observed trajectory.

Algorithm improves transfer learning by inferring successor maps.

New Hessian-free method improves bilevel optimization for meta-learning.

The paper learns particle swarming models from data using Gaussian processes.

The paper translates economic models into a field formalism to study capital accumulation and its fluctuations.

Statistical fields model explains capital allocation and accumulation among firms and investors.

This thesis surveys various metrics on Riemann surface spaces.

Proves existence and uniqueness of weighted metrics for smooth spaces.

New Finsler metrics constructed from $GDW$-metrics.

In this essay, we study the sufficient and necessary conditions for a Randers metrc to be of constant Ricci curvature without the restriction of strong convexity (regularity). The classification result for the case $\|β\|_α>1$ is provided, which is similar to the famous Bao-Robles-Shen's result for strongly convex Rand…

We prove the equivalences of several classical complete metrics on the Teichmüller and the moduli spaces of Riemann surfaces. We use as bridge two new Kähler metrics, the Ricci metric and the perturbed Ricci metric and prove that the perturbed Ricci metric is a complete Kähler metric with bounded negative holomorphic s…

New metric defined for bounded symmetric domains.

Introduces Finslerian convolution metrics and their properties.

New balanced metrics introduced for SPD matrices, improving metric choice.

Survey of recent metric geometry in Kähler metrics space.

Study on geodesics of Finsler metrics derived from Riemannian metrics.

We consider geometries on the space of Riemannian metrics conformally equivalent to the widely studied Ebin L^2 metric. Among these we characterize a distinguished metric that can be regarded as a generalization of Calabi's metric on the space of Kähler metrics to the space of Riemannian metrics, and we study its geome…

New Kähler metrics generalize Calabi's and relate to Fano manifolds.

New Finsler metrics defined by Riemannian and 1-forms are studied.

We study the geodesic equation for the Dirichlet (gradient) metric in the space of Kaehler potentials. We first solve the initial value problem for the geodesic equation of the combination metric, including the gradient metric. We then discuss a comparison theorem between it and the Calabi metric. As geometric motivati…

Study on special Finsler metrics with conditions for Riemannian and isotropic properties.

Sharp estimates for Finsler metrics in convex domains.

The study examines Lee metrics on groups and their properties.

Survey of spectral, probabilistic, and deep metric learning methods.

Study shows convergence of Lagrangian submanifolds under certain metrics.

In this paper, we study an important class of Finsler metrics--square metrics. We give two expressions of such metrics in terms of a Riemannian metric and a 1-form. We show that Einstein square metrics can be classified up to the classification of Einstein Riemannian metrics.

Defines a new Randers metric based on an existing one.

Investigates O(n)-invariant metrics on SPD matrices, extending kernel metrics.

Study Kähler-Einstein metrics on singular varieties, proving metric completion properties.

The current paper deals with some new classes of Finsler metrics with reversible geodesics. We construct weighted quasi-metrics associated with these metrics. Further, we investigate some important geometric properties of weighted quasi-metric space. Finally, we discuss the embedding of quasi-metric spaces with general…

Douglas metrics are metrics with vanishing Douglas curvature which is an important projective invariant in Finsler geometry. To find more Douglas metrics, in this paper we consider a class of Finsler metrics called general $(α,β)$-metrics, which are defined by a Riemannian metric $α=\sqrt{a_{ij}(x)y^iy^j}$ and a $1$-fo…

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

In this paper, we give two classes of positive semi-definite metrics on 2-manifolds. The one is called a class of Kossowski metrics and the other is called a class of Whitney metrics: The pull-back metrics of wave fronts which admit only cuspidal edges and swallowtails in $\boldsymbol{R}^3$ are Kossowski metrics, and t…

In this paper, we introduce the notion of Einstein-reversibility for Finsler met- rics. We study a class of p-power Finsler metrics determined by a Riemann metric and 1-form which are of Einstein-reversibility. It shows that such a class of Finsler metrics of Einstein-reversibility are always Einstein metrics. In parti…

metric-learn simplifies metric learning in Python.

Introduces new metric for Riemannian metrics, extending unbalanced optimal transport.

Study rough Riemannian metrics on manifolds, proving their connectedness and completeness.

Generalizes Thurston's asymmetric metric to flat metrics.