Splash photo of Stanford
Conference on Parsimony and Learning (CPAL)
March 2026, Tübingen

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.

Call for Papers

We are pleased to announce the Third Conference on Parsimony and Learning, to be held in Tübingen, Germany!

Paper submissions for the third Conference on Parsimony and Learning will be opened soon. Please see the call for papers for details about the submission and reviewing process, as well as subject areas of interest and general policies.

Stay tuned for further updates!

Key Dates and Deadlines (Tentative)

All deadlines are 23:59 Anywhere-on-Earth (AOE)

  • 3rd Week of November, 2025: Submission Deadline
  • 1st Week of Jan, 2026: Rebuttal
  • January 31st, 2026: Decisions Released
  • Week of March 23rd 2026: Conference in-person, Tübingen, Germany

Keynote Speakers

Francis Bach

INRIA - École Normale Supérieure

Niao He

ETH Zurich

Bernhard Schölkopf

Max Planck Institute for Intelligent Systems

Taiji Suzuki

University of Tokyo / RIKEN AIP