The progress in science and engineering increasingly depends on our ability to analyze massive amounts of observed and simulated data. The vast majority of this data, coming from high-performance high ...

Patents are valuable for the generation of novel ideas through technological discovery. In recent years, scientists have made ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Machine learning algorithms have gained fame for being able to ferret out ...

Objective: The identification of gene-gene interactions has been limited by small sample size and large number of potential interactions between genes. To address this issue, Ritchie et al. [2001] ...

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on creating an approximation of a dataset that has fewer columns. Imagine that you have a dataset that has many ...

Quasi—Monte Carlo (QMC) methods are important numerical tools in the pricing and hedging of complex financial instruments. The effectiveness of QMC methods crucially depends on the discontinuity and ...

Imaging of tissue specimens is an important aspect of translational research that bridges the gap between basic laboratory science and clinical science to improve the understanding of cancer and aid ...

Marketers must be deliberate when adding dimensions to a machine learning model. The cost of adding too many is accuracy. Decluttering fever is sweeping the country thanks to Marie Kondo. But clutter ...

Identifying and interpreting vacancies in patent maps is a promising approach to discover technological opportunities.