What dataset features affect machine learning (ML) performance has primarily been unknown in the current literature. This study examines the impact of tabular datasets' different meta-level and ...

The rising popularity of electric vehicles (EVs) is driving a transition in transportation toward electric vehicles (EVs), which presents both opportunities and problems for energy management systems.

This paper comprehensively surveys existing works of chip design with ML algorithms from an algorithm perspective. To accomplish this goal, the authors propose a novel and systematical taxonomy for ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle collisions at the LHC. This new approach can reconstruct collisions more quickly ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...