3 papers
cs.LG2026
The Kalman Evolve: Closing the Gap in Kalman Filtering via Interpretable Algorithm Discovery
Vasileios Saketos, Ming Xiao
State estimation is a fundamental problem in control and signal processing, for which the Kalman Filter provides an optimal solution under linear dynamics, Gaussian noise, and know…
stat.ML2026
Minimizing Human Intervention in Online Classification
William Réveillard, Vasileios Saketos, Alexandre Proutiere +1
Training or fine-tuning large language model (LLM)-based systems often requires costly human feedback, yet there is limited understanding of how to minimize such intervention while…
cs.NE2025
Data-Driven Discovery of Interpretable Kalman Filter Variants through Large Language Models and Genetic Programming
Vasileios Saketos, Sebastian Kaltenbach, Sergey Litvinov +1
Algorithmic discovery has traditionally relied on human ingenuity and extensive experimentation. Here we investigate whether a prominent scientific computing algorithm, the Kalman…