Unsolved Problems in Human-in-the-Loop Machine Learning

Explore unsolved problems in human-in-the-loop machine learning in this 36-minute conference talk by Robert Monarch, author of "Human-in-the-Loop Machine Learning." Delve into key topics such as interpreting model uncertainty, recent advances in transfer learning, and improvements in annotation quality control. Discover the implications of intermediate task transfer learning on annotation tasks and workforces. Learn about strategies for identifying annotators with rare but valid subjective interpretations and methods for combining machine learning predictions with human annotations. Gain insights from Monarch's extensive experience in artificial intelligence and his work with major tech companies and diverse global environments.

Unsolved Problems in Human in the Loop Machine Learning