Learning in Networks Reading Group

Learning in Networks Reading Group and Seminar Series: Tuesdays, 12pm in 330 Gross Hall; lunch included
The institute focuses on fundamental questions in statistical inference, machine learning, causal inference, and optimization on networks, with particular emphasis on statistical-computational tradeoffs, message-passing algorithms, learning dynamics, and network-based market design. By fostering collaboration across disciplines, the institute aims to develop new mathematical and algorithmic foundations for understanding complex networked systems and their applications. The institute is led by collaborators Jiaming Xu, Alex Belloni, Fan Wei, Galen Reeves, and James Moody.
Learn more: https://sites.duke.edu/learninginnetworks/