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.
Digital tools may hinder or facilitate multidisciplinary collaboration in occupational health.
Study finds financial constraints explain zero-leverage firms.
The study of solutions with fixed energy of certain classes of Lagrangian (or Hamiltonian) systems is reduced, via the classical Maupertuis--Jacobi variational principle, to the study of geodesics in Riemannian manifolds. We are interested in investigating the problem of existence of brake orbits and homoclinic orbits,…
Uber optimizes marketplace levers using machine learning to improve resource allocation efficiency.
We use a geometric construction to exhibit examples of autonomous Lagrangian systems admitting exactly two homoclinics emanating from a nondegenerate maximum of the potential energy and reaching a regular level of the potential having the same value of the maximum point. Similarly, we show examples of Hamiltonian syste…
ETFs with 2x and 3x leverage underperformed the S&P 500 index due to compounding and volatility.
Motivated by the use of degenerate Jacobi metrics for the study of brake orbits and homoclinics, we develop a Morse theory for geodesics in conformal metrics having conformal factors vanishing on a regular hypersurface of a Riemannian manifold.
AB dynamically scales gradients to mitigate asynchronous training delays.
This work examines the role of reinforcement learning in reducing the severity of on-road collisions by controlling velocity and steering in situations in which contact is imminent. We construct a model, given camera images as input, that is capable of learning and predicting the dynamics of obstacles, cars and pedestr…
In this paper we give a proof of the existence of an orthogonal geodesic chord on a Riemannian manifold homeomorphic to a closed disk and with concave boundary. This kind of study is motivated by the link of the multiplicity problem with the famous Seifert conjecture (formulated in 1948) about multiple brake orbits for…
Strategic feature selection in high-stakes domains like healthcare.
The study assesses the relative value of prediction in algorithmic decision making.
SECRM-2D improves RL-based autonomous driving with safety guarantees.
Innovation is among the key factors driving a country's economic and social growth. But what are the factors that make a country innovative? How do they differ across different parts of the world and different stages of development? In this work done in collaboration with the World Economic Forum (WEF), we analyze the …
We show that the co-rays to a ray in a complete non-compact Finsler manifold contain geodesic segments to upper level sets of Busemann functions. Moreover, we characterise the co-point set to a ray as the cut locus of such level sets. The structure theorem of the co-point set on a surface, namely that is a local tree, …
A modular cash-overlay rule for allocating between a fixed growth-defensive risky sleeve and interest-bearing cash.
This paper prices and replicates the financial derivative whose payoff at is the wealth that would have accrued to a $\$1$ deposit into the best continuously-rebalanced portfolio (or fixed-fraction betting scheme) determined in hindsight. For the single-stock Black-Scholes market, Ordentlich and Cover (1998) only p…
In a crisis of public finances, France bases all its hopes on the "evaluation of performance" to moderate the effects of a complex crisis. Under the banner of "modernization of the State", a new "financial constitution" called the Organic Law on finance laws (LOLF) became the main lever of reform of public management. …
New formula identifies and quantifies costs for automated market makers.
We adopt data structure in the form of cover trees and iteratively apply approximate nearest neighbour (ANN) searches for fast compressed sensing reconstruction of signals living on discrete smooth manifolds. Levering on the recent stability results for the inexact Iterative Projected Gradient (IPG) algorithm and by us…
The study evaluates how prediction helps identify the worst-off in welfare programs.
The paper studies bifurcations in Lagrangian systems and geodesics.
Isotonic regression binning affects calibration statistics of machine learning models.
Paper discovers manoeuvres from vehicle telematics data.
Power system emergency control is generally regarded as the last safety net for grid security and resiliency. Existing emergency control schemes are usually designed off-line based on either the conceived "worst" case scenario or a few typical operation scenarios. These schemes are facing significant adaptiveness and r…
QBC uses quantum computers to speed up Bayesian computation.
Optimizes AMM markets with a new framework reducing complex optimization to simpler root finding.
A reliable controller is critical and essential for the execution of safe and smooth maneuvers of an autonomous vehicle.The controller must be robust to external disturbances, such as road surface, weather, and wind conditions, and so on.It also needs to deal with the internal parametric variations of vehicle sub-syste…
DeepHybrid uses radar data to classify objects accurately.
Variable speed limits (VSL) control is a flexible way to improve traffic condition,increase safety and reduce emission. There is an emerging trend of using reinforcement learning technique for VSL control and recent studies have shown promising results. Currently, deep learning is enabling reinforcement learning to dev…
Advanced driver assistance systems (ADAS) can be significantly improved with effective driver action prediction (DAP). Predicting driver actions early and accurately can help mitigate the effects of potentially unsafe driving behaviors and avoid possible accidents. In this paper, we formulate driver action prediction a…
Data generated by cars is growing at an unprecedented scale. As cars gradually become part of the Internet of Things (IoT) ecosystem, several stakeholders discover the value of in-vehicle network logs containing the measurements of the multitude of sensors deployed within the car. This wealth of data is also expected t…
The paper detects adversarial examples in LECs for regression in CPS using variational autoencoder.
Paper introduces DP methods for high-dimensional variable selection.
One of the most exciting technology breakthroughs in the last few years has been the rise of deep learning. State-of-the-art deep learning models are being widely deployed in academia and industry, across a variety of areas, from image analysis to natural language processing. These models have grown from fledgling rese…
Predicting the health of components in complex dynamic systems such as an automobile poses numerous challenges. The primary aim of such predictive systems is to use the high-dimensional data acquired from different sensors and predict the state-of-health of a particular component, e.g., brake pad. The classical approac…
CurveRL optimizes large model reasoning by reweighting prompts based on their rank and density.
The paper analyzes LETF option markets using moneyness scaling to find statistical arbitrage opportunities.
Survival strategy for crypto firms in bear markets using BTC-to-sats payments rail.
New algorithms improve stopping time for best arm identification.
AuON is a linear-time optimizer that improves upon Muon's performance without approximate orthogonal matrices.
Review and benchmark 58 feature selection methods for ML applications.
Improved risk assessment for UBI using telematics data and AdaBoost.
IDA makes DFMM's asset tradeable, enhancing cross-chain finance efficiency.
We present another view dealing with the Arnold-Givental conjecture on a real symplectic manifold with nonempty and compact real part . For given and we show the equivalence of the following two claims: (i) for any Hamiltonia…
SAGE improves memory efficiency by selectively adding, merging, or ignoring new facts.
Real-time detection of out-of-distribution data in CPS control systems.
This paper explains CART random forests using stochastic control theory.