Lecture
This lecture covers the topic of online matching in evolving environments, focusing on the challenges and solutions for adapting algorithms to changing data over time. The instructor discusses the use of randomization, dynamic matching, and the concept of instance optimality. Various algorithms and techniques are explored, including the application of negative association theory and the development of adaptive online algorithms. The presentation also delves into the implications of adaptive data on algorithm design and the quest for instance-optimal solutions.