Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting?

Active learning represents a transformative paradigm in machine learning, aimed at reducing the annotation burden by selectively querying the most informative data points. This approach leverages ...

Inspired by how the human brain consolidates memory, the 'Nested Learning' framework allows different parts of a model to learn and update at different speeds.

In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing, ...

AI is not limited to diagnostics or imaging. It also plays a transformative role in biomedical research, computational ...

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 ...

Machine learning is based on the idea that a system can learn to perform a task without being explicitly programmed. Machine learning has a wide range of applications in the finance, healthcare, ...

New research finds that machine-learning algorithms can help health care staff distinguish the two conditions. Researchers show how algorithms may be effective predictive tools using a few simple ...

Humans have struggled to make truly intelligent machines. Maybe we need to let them get on with it themselves. A little stick figure with a wedge-shaped head shuffles across the screen. It moves in a ...

William Brady does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond ...