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.
ReSkill reconciles RL skill creation with policy optimization.
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.
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.
AI+MPS workshop aims to strengthen AI's role in science.
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…
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…
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.