The Conference on Parsimony and Learning (CPAL) is an annual research conference focused on addressing the parsimonious, low-dimensional structures that prevail in machine learning, signal processing, optimization, and beyond. We are interested in theories, algorithms, applications, hardware, and systems, as well as scientific foundations for learning with parsimony.

Keynote Speakers

• Alison Gopnik, University of California, Berkeley
• Fred Kjolstad, Stanford University
• Jason Lee, Princeton University
• Konrad Kording, University of Pennsylvania
• Michael Unser, École Polytechnique Fédérale de Lausanne (EPFL)
• Richard Baraniuk, Rice University
• Yuandong Tian, Meta AI Research

Visit the CPAL website for key dates, confirmed speakers, and more information.