EVOLVE, an agentic framework that autonomously optimizes AI training data, model architectures, and learning algorithms — ...

When a quantum computer processes data, it must translate it into understandable quantum data. Algorithms that carry out this 'quantum compilation' typically optimize one target at a time. However, a ...

Researchers have introduced an online model-based reinforcement learning algorithm that trains robots directly from real-world interactions, bypassing extensive simulation. The approach builds a ...

Supervised learning algorithms learn from labeled data, where the desired output is known. These algorithms aim to build a model that can predict the output for new, unseen input data. Let’s take a ...

Human social learning is increasingly occurring on online social platforms, such as Twitter, Facebook, and TikTok. On these platforms, algorithms exploit existing social-learning biases (i.e., towards ...

As the use of machine learning algorithms in health care continues to expand, there are growing concerns about equity, fairness, and bias in the ways in which machine learning models are developed and ...

Concurrent durvalumab plus chemoradiation therapy followed by durvalumab in Chinese patients with unresectable stage III non-small cell lung cancer: CRUISER study. This is an ASCO Meeting Abstract ...

When it comes to teaching math, a debate has persisted for decades: How, and to what degree, should algorithms be a focus of learning math? The step-by-step procedures are among the most debated ...