17-740 Algorithmic Foundations of Interactive Learning

12 units, Carnegie Mellon University

Interactive learning is a dynamic approach to machine learning where systems learn and adapt through continuous interaction with their environment or users, receiving feedback and adjusting their behavior in real time. These techniques are currently experiencing a resurgence across various domains of artificial intelligence and machine learning, from robotics to language modeling. In this advanced theory course, students will explore interactive learning from its foundational principles to recent applications, including finetuning Large Language Models LLMs and robot learning from demonstration.

Prerequisites: none listed

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