Explore advanced privacy concepts in this comprehensive tutorial delivered by Adam Smith from Boston University and Lydia Zakynthinou from Johns Hopkins University as part of the Federated and Collaborative Learning Boot Camp. Delve into sophisticated privacy-preserving techniques and theoretical foundations that build upon fundamental privacy principles, examining how these concepts apply specifically to federated and collaborative learning environments. Learn about cutting-edge research developments, mathematical frameworks, and practical implementations that address privacy challenges in distributed machine learning systems. Gain insights into the latest methodologies for protecting sensitive data while enabling effective collaboration across multiple parties in machine learning scenarios.