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.
New method forecasts workforce reintegration success rates.
Strategic Workforce Planning is a company process providing best in class, economically sound, workforce management policies and goals. Despite the abundance of literature on the subject, this is a notorious challenge in terms of implementation. Reasons span from the youth of the field itself to broader data integratio…
Study finds macroeconomic indicators predict health workforce and infrastructure measures.
AI+MPS workshop aims to strengthen AI's role in science.
Optimizes task allocation for financial analysts to balance work efficiency and well-being.
New AI model optimizes personalized care for elderly residents.
AI monitors social distancing and masks at manufacturing plants.
The paper aims to explore the impacts of bi-demographic structure on the current account and growth. Using a SVAR modeling, we track the dynamic impacts between these underlying variables. New insights have been developed about the dynamic interrelation between population growth, current account and economic growth. Th…
Proposes a Big Data framework for SC forecasting, including data preprocessing and machine learning.
Paper uses Monte Carlo simulations to predict retirement portfolios.
We introduce a simple agent-based model which allows us to analyze three stylized facts: a fat-tailed size distribution of companies, a `tent-shaped' growth rate distribution, the scaling relation of the growth rate variance with firm size, and the causality between them. This is achieved under the simple hypothesis th…
The number of Italian firms in function of the number of workers is well approximated by an inverse power law up to 15 workers but shows a clear downward deflection beyond this point, both when using old pre-1999 data and when using recent (2014) data. This phenomenon could be associated with employent protection legis…
The recent wave of AI and automation has been argued to differ from previous General Purpose Technologies (GPTs), in that it may lead to rapid change in occupations' underlying task requirements and persistent technological unemployment. In this paper, we apply a novel methodology of dynamic task shares to a large data…
Machine learning models learn what we teach them to learn. Machine learning is at the heart of recommender systems. If a machine learning model is trained on biased data, the resulting recommender system may reflect the biases in its recommendations. Biases arise at different stages in a recommender system, from existi…
Sales forecast is an essential task in E-commerce and has a crucial impact on making informed business decisions. It can help us to manage the workforce, cash flow and resources such as optimizing the supply chain of manufacturers etc. Sales forecast is a challenging problem in that sales is affected by many factors in…
This work uses reinforcement learning to optimize task scheduling and execution in a dynamic multi-agent warehouse environment.
Dual labor market model explains low inflation despite low unemployment.
HOFLON automates process start-ups and grade-changes using offline RL and online optimization.
Curves can bound only finitely many developable surfaces.
The paper extends Cartan development to infinite dimensional Lie groups.
The paper studies singularities on parallels of tangent developable surfaces of frontal curves.
Survey on new Ricci flow techniques.
Survey of software developers' experience with Github Copilot tool.
We provide a condition for spatial curves which rules out the development of a type I singularity. The condition is that after the last time for which an inflection point develops, if the torsion is ever everywhere non-negative, the curve cannot develop a type I singularity.
PrototypeML simplifies neural network design and development.
Survey on DDVV-type inequalities, their history, and recent developments.
Study on insurance risk management and sustainable development.
This manuscript develops the theory of agglomerative clustering with Bregman divergences. Geometric smoothing techniques are developed to deal with degenerate clusters. To allow for cluster models based on exponential families with overcomplete representations, Bregman divergences are developed for nondifferentiable co…
We develop a method to describe laws of random surfaces using surface holonomy.
This paper reviews the checkered history of predictive distributions in statistics and discusses two developments, one from recent literature and the other new. The first development is bringing predictive distributions into machine learning, whose early development was so deeply influenced by two remarkable groups at …
Study shows 'Belt and Road' node cities boost digital finance in China.
Establishes existence of maximal globally hyperbolic development for Einstein equations.
We investigate the relationship among characteristic curves on developable surfaces. In case parameter curves coincide with these curves, we show that the base curve of a developable surface could be either a plane curve, a circular helix, a general helix or a slant helix.
Motivated by applications in architecture and design, we present a novel method for increasing the developability of a B-spline surface. We use the property that the Gauss image of a developable surface is 1-dimensional and can be locally well approximated by circles. This is cast into an algorithm for thinning the Gau…
This article presents a theoretical model for a dynamic system based on sustainable development. Due to the relatively absence of theoretical studies and practical issues in the area of sustainable development, Romania aspires to the principles of sustainable development. Based on the concept as a process in which econ…
Simplifying machine learning (ML) application development, including distributed computation, programming interface, resource management, model selection, etc, has attracted intensive interests recently. These research efforts have significantly improved the efficiency and the degree of automation of developing ML mode…
Recent developments in Seiberg-Witten theory and relations with Complex Geometry.
This paper presents a simple model to measure the relative economic growth of economic systems. The model considers S-Shaped patterns of economic growth that, represented with a linear model, measure how an economic system grows in comparison with another one. In particular, this model introduces an approach which indi…
Constructs stochastic processes on sub-Riemannian manifolds using Cartan connections.
This article reports recent developments of the research on Hamilton's Ricci flow and its applications.
This chapter focuses on developing datasets for machine learning, addressing data preparation challenges.
The paper develops a causal machine learning framework to optimize aid allocation.
Defines metrics for Lorentzian spaces and explores maximal developments.
In this paper, the Almeida-Molino obstruction to developability of transversely complete foliations is extended to Lie groupoids.
The paper analyzes the current state of the world economy and offers a short-term forecast of its development. Our analysis of log-periodic oscillations in the DJIA dynamics suggests that in the second half of 2017 the United States and other more developed countries could experience a new recession, due to the third p…
In this paper we do the first large scale analysis of writing style development among Danish high school students. More than 10K students with more than 100K essays are analyzed. Writing style itself is often studied in the natural language processing community, but usually with the goal of verifying authorship, assess…
Proposes guidelines for developing medical AI products.
Framework for AI healthcare products from concept to market.