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.
We describe our vision for the conference in more detail here.
Call for Papers
We are pleased to invite paper submissions for the first Conference on Parsimony and Learning. 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
- August 28th, 2023: Submission Deadline for Proceedings Track
- October 10th, 2023: Submission Deadline for Recent Spotlight Track
- October 14th, 2023: 2-Week Rebuttal Stage Starts (Proceedings Track)
- October 27th, 2023: Rebuttal Stage Ends, Authors-Reviewers Discussion Stage Starts (Proceedings Track)
- November 5th, 2023: Authors-Reviewers Discussion Stage Ends (Proceedings Track)
- November 20th, 2023: Final Decisions Released (Both Tracks)
- December 5th, 2023: Camera-Ready Deadline (Both Tracks)
- January 3rd-6th, 2024: Main Conference (In-Person, HKU Main Campus)
Keynote Speakers
Additional speakers to be announced soon!
Dan Alistarh
IST Austria / Neural Magic
SueYeon Chung
NYU / Flatiron Institute
Tom Goldstein
University of Maryland
Yingbin Liang
Ohio State University
Robert D. Nowak
University of Wisconsin-Madison
Dimitris Papailiopoulos
University of Wisconsin-Madison
Jong Chul Ye
KAIST