Online algorithms are central to solving resource allocation and matching challenges in dynamic environments where decisions must be made without complete knowledge of future events. Research in this ...

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 ...

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 ...

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT, ...

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 ...