Tyler Jarvis, Brigham Young University professor, will be visiting the UO Math Department on May 13 and 14 and giving two talks as part of the Niven Lectures.
At 4 pm Wednesday, May 13, Jarvis will present the lecture "Aliasing in Linear Regression: New Insights into a Fundamental Tool" intended for undergraduate students. The lecture will cover the phenomenon called aliasing, which occurs in many settings, including in a fundamental tool of science, statistics, and machine learning called linear regression.
At 4 pm May 14, Jarvis will discuss "Learning and Reasoning under Certainty with Relative Entropy," aimed for a general math audience. Most AI and machine learning problems are also issues related to updating probabilities with new information. The most important and most general rule is minimizing relative entropy. Explore more about Jarvis' argument at 128 Chiles Hall.
Jarvis is co-founder and director of the Applied and Computational Math (ACME) program at BYU, which was recognized as the American Mathematical Society's 2024 Exemplary Program in Mathematics. He is author of two books on applied mathematics and has worked on a wide range of research problems including in mathematical foundations of machine learning, mathematical modeling of physiological signals, mathematical analysis of redistricting and gerrymandering, and questions in algebraic geometry arising from high-energy physics.