Learning Ising Models from One, Ten or a Thousand Samples

Learning Ising Models from One, Ten or a Thousand Samples

Explore the intricacies of learning Ising models from varying sample sizes in this hour-long lecture by MIT's Costis Daskalakis. Delve into the challenges and techniques of learning and testing in high-dimensional spaces, focusing on the impact of sample quantity on model accuracy and efficiency. Gain insights into the mathematical foundations and practical applications of Ising models across different disciplines.