Abstract: Many constrained control problems in queueing and scheduling admit elegant structures, yet reinforcement learning methods rarely exploit them. In this talk, I will present a framework for structured reinforcement learning that […]

We have the pleasure to have Lasse Vursteen (Duke University) presenting his work on Optimality Theory for Adaptive Federated Estimation under Differential Privacy (via Teams). Abstract: This talk addresses adaptive density estimation […]

We are delighted to welcome Amir Asadi from University of Cambridge to talk about their work. Title: Multiscale Machine Learning: An Information-Theoretic Approach Abstract: Machine learning models draw on two fundamental […]

Bio: Dr. Yuting Wei is an Associate Professor in the Statistics and Data Science Department at the Wharton School, University of Pennsylvania. Prior to that, Dr. Wei spent two years […]

András György is a Senior Staff Research Scientist at Google DeepMind, London, UK. He received his Ph.D. from the Budapest University of Technology and Economics, Hungary. He was a postdoctoral […]