Koopman-Based Generalization Bounds in Multi-Task Deep Learning

This ArXiv paper explores the theoretical underpinnings of generalization in multi-task deep learning, leveraging the Koopman operator. Understanding generalization is crucial for the reliability and applicability of these models across diverse tasks.

• •Focuses on theoretical bounds for generalization.
• •Applies Koopman operator to multi-task learning.
• •Important for model reliability.