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.
The paper extends the Manhattan curve concept to complex dynamics and studies its relation to multiplier spectra.
The Manhattan curve connects metrics of hyperbolic groups, showing rigidity.
In this paper, we extend the construction of pressure metrics to Teichmüller spaces of surfaces with punctures. This construction recovers Thurston's Riemannian metric on Teichmüller spaces. Moreover, we prove the real analyticity and the convexity of Manhattan curves of the finite area type-preserving Fuchsian represe…
This study uses Twitter to analyze traveler behavior in Manhattan.
A method for camera calibration using heatmap regression for fisheye images.
Strict concavity proven for growth indicator function of certain groups.
Develops correlation number for specific potentials and Hitchin representations.
Study shows exact dimensionality and regularity of manifolds for specific groups.
Paper refines cross-lingual word embeddings using Manhattan norm.
New method proves length spectrum rigidity in various geometric settings.
The paper studies the correlation of Hilbert lengths for convex projective surfaces.
Geodesics and boundaries found for metric structures on hyperbolic groups.
Non-negative matrix factorization (NMF) approximates a non-negative matrix by a product of two non-negative low-rank factor matrices and . NMF and its extensions minimize either the Kullback-Leibler divergence or the Euclidean distance between and to model the Poisson noise or the Gaussian noise.…
Finding the reduced-dimensional structure is critical to understanding complex networks. Existing approaches such as spectral clustering are applicable only when the full network is explicitly observed. In this paper, we focus on the online factorization and partition of implicit large-scale networks based on observati…
The economy globalization measure problem is discussed. Four macroeconomic indices of twenty among the "richest" countries are examined. Four types of "distances" are calculated.Two types of networks are next constructed for each distance measure definition. It is shown that the globalization process can be best charac…
Using publicly available traffic camera data in New York City, we quantify time-dependent patterns in aggregate pedestrian foot traffic. These patterns exhibit repeatable diurnal behaviors that differ for weekdays and weekends but are broadly consistent across neighborhoods in the borough of Manhattan. Weekday patterns…
A Discriminative Deep Forest (DisDF) as a metric learning algorithm is proposed in the paper. It is based on the Deep Forest or gcForest proposed by Zhou and Feng and can be viewed as a gcForest modification. The case of the fully supervised learning is studied when the class labels of individual training examples are …
In this paper we introduce three methods for re-scaling data sets aiming at improving the likelihood of clustering validity indexes to return the true number of spherical Gaussian clusters with additional noise features. Our method obtains feature re-scaling factors taking into account the structure of a given data set…
Study analyzes Airbnb booking lead times during global crises using a new metric.
The paper estimates key metrics for linear models with Markov or hidden Markov sources.
The rise in popularity of major social media platforms have enabled people to share photos and textual information about their daily life. One of the popular topics about which information is shared is food. Since a lot of media about food are attributed to particular locations and restaurants, information like spatio-…
Generative modeling on metric graphs using neural optimal transport
Study confirms fractional norms and quasinorms do not help overcome curse of dimensionality.
We propose a new class of metrics on sets, vectors, and functions that can be used in various stages of data mining, including exploratory data analysis, learning, and result interpretation. These new distance functions unify and generalize some of the popular metrics, such as the Jaccard and bag distances on sets, Man…
This paper develops a low-nonnegative-rank approximation method to identify the state aggregation structure of a finite-state Markov chain under an assumption that the state space can be mapped into a handful of meta-states. The number of meta-states is characterized by the nonnegative rank of the Markov transition mat…
State aggregation is a popular model reduction method rooted in optimal control. It reduces the complexity of engineering systems by mapping the system's states into a small number of meta-states. The choice of aggregation map often depends on the data analysts' knowledge and is largely ad hoc. In this paper, we propos…
In this paper, a novel joint transmit power and resource allocation approach for enabling ultra-reliable low-latency communication (URLLC) in vehicular networks is proposed. The objective is to minimize the network-wide power consumption of vehicular users (VUEs) while ensuring high reliability in terms of probabilisti…
The article proposes modified Gower's coefficients for handling mixed type variables in nearest neighbor methods.
MuJAM learns traffic signal control policies that generalize to unseen intersections and traffic conditions.
IG-RL learns adaptive traffic signals for any network, outperforming existing methods.
Study of group actions on CAT(0) cube complexes, focusing on marked length spectra.
We prove contractibility of VR complexes for integer lattices up to dimension 5.