Abstract: In a recent paper [1], we introduced the fuzzy Bayesian learning paradigm where expert opinions can be encoded in the form of fuzzy rule bases and the hyper-parameters of the fuzzy sets can ...

Abstract: Data-driven techniques such as principal component analysis (PCA) have been widely used to derive predictive models from historical data and applied for quality prediction in industry.

Clay Halton was a Business Editor at Investopedia and has been working in the finance publishing field for more than five years. He also writes and edits personal finance content, with a focus on ...

In the predawn hours of August 19, 2024, bolts of lightning began to fork through the purple-black clouds above the Mediterranean. From the rail of a 184-foot vessel, a 22-year-old named Matthew ...

In this blog post, I am going to teach you how to train a Bayesian deep learning classifier using Keras and tensorflow. Before diving into the specific training example, I will cover a few important ...

While the performance of current AI systems may seem impressive, there's a long way to go before we're likely to see true human-like capabilities. AI is everywhere – or so you might be forgiven for ...

Understanding the interplay between network architecture, dataset statistics, and learning algorithms is a key challenge in deep learning. We overcome this challenge analytically for zero-noise ...

A full-code demo from Dr. James McCaffrey of Microsoft Research shows how to predict the type of a college course by analyzing grade counts for each type of course. General naive Bayes classification ...

Randomized controlled trials are considered the golden standard for estimating treatment effect but are costly to perform and not always possible. Observational data, although readily available, is ...

It has been more than 50 years since astronomers first proposed “dark matter”, which is thought to be the most common form of matter in the universe. Despite this, we have no idea what it is – nobody ...