series models and offline and online machine learning (ML) techniques in a standard data science approach. We chose to …

performing (full) grid searches on the parameters lack efficiency, we propose a machine learning enhanced grid search. To that …

indirect methods to infer its condition. Past research approaches utilized a plethora of machine learning models to infer the …

This study investigates the predictive power of CEO characteristics on accounting fraud utilizing a machine learning … employ five machine learning models well-established in the accounting fraud literature. Diverging from prior studies, we … approach. Grounded in upper echelons theory, we show the predictive value of widely neglected CEO characteristics for machine …

implement a machine learning approach. This paper discusses the general foundation of the heuristic and the algorithm while two …

' informational inefficiency. The relative contribution of machine learning is higher for artists with less dispersed and lower …

largely unknown. This paper uses machine learning on regulatory documents to construct a novel dataset on compliance costs to …

that have been deployed on the Ethereum blockchain and have been involved in 317,950 sales using machine learning methods …