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CPAL OpenReview

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

Update: The proceedings track submission deadline has been extended by one week to December 12th, 2025 (AOE).

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 are now open! Please see the call for papers for details about the submission and reviewing process, as well as subject areas of interest and general policies.

Submit Your Work on OpenReview

Call for Tutorials

CPAL 2026 invites proposals for in-person tutorials on advancing our understanding of intelligence through the lens of parsimonious learning and its various facets. We welcome tutorials on theories of parsimonious learning, algorithms and implementations, applications in various domains, hardware and systems for efficient learning, and scientific foundations and connections to other fields.

Tutorial proposal deadline: December 10, 2025

Please see the call for tutorials for submission guidelines and details.

Rising Stars Award

The CPAL Rising Stars Award program highlights exceptional junior researchers at a critical inflection point in their career: last-year PhD students, postdoctoral scholars, first-year tenure track faculty, or industry researchers within two years of graduation. Selected awardees will receive a full registration waiver and participate in dedicated poster sessions, panels, and networking opportunities with senior researchers.

Application deadline: December 15, 2025

Please see the call for applications for eligibility criteria and application requirements.