Algorithmic biases have become a hot-button issue in global society. This is especially acute now with the effective date for GDPR compliance fast approaching and everybody racing to institute a ...

In machine learning, it is often necessary to statistically compare the overall performance of two algorithms (e.g., our proposed algorithm and each compared baseline) based on multiple benchmark ...

The expectation-maximization (EM) algorithm is a cornerstone technique for parameter estimation in statistical models that incorporate latent variables or incomplete data. By iteratively alternating ...

We've reviewed in an earlier article Daniel Kahnemann's Prospect Theory, his latest book quot;Thinking Fast and Slowquot; and some of the key findings of Behavioural Finance and we'll be discussing a ...

In the 21st century, artificial intelligence (AI) has emerged as a valuable approach in data science and a growing influence in medical research, 4-6 with an accelerating pace of innovation. This ...

In 2013, a man named Eric L. Loomis was sentenced for eluding police and driving a car without the owner’s consent. When the judge weighed Loomis’ sentence, he considered an array of evidence, ...

Data analysis and machine learning are finding applications in many fields of fundamental sciences, and theoretical physics is no exception. My group at the Institut de Physique Théorique (IPhT) ...