In this talk, I will present results on the algorithmic randomness and dimension of points on lines in the Euclidean plane and address relationships between geometric notions of size and computational notions of predictability and compressibility. A key relationship is the Point-to-Set Principle, by which local Kolmogorov complexity bounds yield global fractal dimension bounds. I will also discuss implications for robustness and replicability.
Neil Lutz,
University of Pennsylvania
Neil Lutz is a visiting assistant professor of computer science at Swarthmore College, a lecturer in the Department of Computer and Information Science at the University of Pennsylvania, and an affiliate assistant professor of computer science at Iowa State University. His research interests include algorithmic information theory, geometric measure theory, and fairness in multi-agent systems. He holds a Ph.D. in computer science, supervised by Rebecca Wright. Prior to his current roles, Neil was a postdoctoral researcher at the University of Pennsylvania, where he worked with Sampath Kannan.