No Free Lunch in Machine Learning? Xiao-Li Meng Explains скачать в хорошем качестве

No Free Lunch in Machine Learning? Xiao-Li Meng Explains

Keynote Lecture by Prof. Xiao-Li Meng (Harvard University) - Thursday, October 2, 2pm. Title: No Free Lunch: From a Simultaneous (Machine) Learning Impossibility to Heisenberg Uncertainty Principle. In this seminar, Prof. Meng explores the fundamental trade-offs at the core of statistical learning: Why is it impossible to achieve both optimal learning and accurately assess learning error using the same data? How does the “no free lunch” principle mirror deep scientific constraints like the Cramér-Rao bound and the Heisenberg uncertainty principle? What do these universal limits mean for artificial intelligence and data-driven discovery? This keynote lecture is a featured session of the Hi! PARIS AI Seminar Cycle, a monthly series that brings together leading voices in AI and Data Science. The cycle provides a platform to foster interdisciplinary exchange and highlight AI’s scientific, business, and societal impact. 👉 See upcoming Hi! PARIS seminars: https://www.hi-paris.fr/2025/09/26/ai... #machinelearning #datascience #artificialintelligence