Machine learning, or as it is also called automated learning, is a special subfield of scientific information technologies. The name "machine learning" refers to the automated detection of meaningful patterns in large data sets. Machine learning is gaining importance in many different areas of...

The application to people of prediction algorithms, especially ones based on statistical classifier methods, can be perilous — and not only when limitations, bias and systemic effects are ill-understood by those using them as has often been the case. This is topical as such methods, sometimes...

This Comment is written in response to DOJ-FTC Request for Information on Merger Enforcement. We explain that the use of pricing algorithms based on artificial intelligence methodologies (hereinafter: "pricing algorithms"), by one or both parties, should be taken into account in the merger...

This paper evaluated the performance of the numerical integration methods applied to the transient multiphysics reactor core models. The models were integrated by the Backward Difference Formula (BDF) with automatic order and step size selection. The in-step non-linear system was solved by the...

This paper examines the impact of algorithmic trading (AT) on investors’ incentives to initiate block ownership in U.S. public companies. We find that a one standard deviation change in AT activity reduces the block ownership initiation likelihood by 3.5%. Using the SEC’s randomised tick...