MARS Seminar: Jixiang Qing (Lancaster)

Event Details

MARS seminar series | Speaker: Jixiang Qing (Lancaster) | Title: Self Induced Active Learning under Gaussian Processes

Abstract: Many real-world problems involve learning tasks where prediction accuracy is not equally important across the input space, but instead matters most in regions determined by the unknown function itself. When function evaluations are expensive, how can we learn efficiently without knowing these regions in advance? In this talk, we formalize this problem from an active learning perspective, focusing on Gaussian process regression under self-induced Boltzmann distributions. We introduce a novel acquisition strategy that approximates the unknown target distribution without estimating its partition function, while balancing exploration and weighted variance reduction. We present theoretical convergence guarantees and demonstrate the effectiveness of the proposed method on synthetic benchmarks and real-world applications in computational chemistry and drug discovery.