CPAL 2027 — Fourth Conference on Parsimony and Learning
by Conference on Parsimony and Learning (CPAL)
The research conference on sparsity, low rank and efficient structure in machine learning — Tokyo 2027
About This Event
CPAL 2027, the fourth Conference on Parsimony and Learning, runs 23–26 March 2027 at Hitotsubashi Hall in Tokyo, Japan. It is an annual research conference on the parsimonious, low-dimensional structures that prevail in machine learning, signal processing and optimization — sparsity, low rank, symmetry, modularity, compressibility and structured computation. General chairs are Yi Ma (University of Hong Kong) and Taiji Suzuki (University of Tokyo and RIKEN AIP), and keynotes come from Yuejie Chi, Kenji Fukumizu, Yew-Soon Ong and Masashi Sugiyama. The programme combines an archival Proceedings Track published in PMLR, a non-archival Recent Spotlight Track, tutorials and a Rising Stars Award, organised under three subject areas: theory and foundations; methods and models; and systems, data and applications. The 2026 edition was held in Tübingen.
Key Dates & Deadlines
- Proceedings track abstract registration
- Proceedings track paper deadline
- Tutorial proposal deadline
- Rising Stars Award application deadline
- Reviews released; rebuttal begins
- Tutorial proposal results announced
- Rebuttal period ends
- Recent Spotlight Track submission deadline
- Rising Stars Award notification
- Author–reviewer discussion ends
- Notification to authors (proceedings and spotlight)
- Camera-ready deadline
At a Glance
- Date
- March 23–26, 2027
- Location
- Hitotsubashi Hall, Tokyo, Japan
- Format
- In-Person
- Event Type
- Conference
- Status
- Upcoming
- Pricing
- Paid
- Organizer
- Conference on Parsimony and Learning (CPAL)
- Added
- Sep 14, 2026
- Updated
- Sep 14, 2026
Topics & Focus Areas
Who Should Attend
- ✓Machine learning researchers
- ✓Heads of AI infrastructure and model efficiency
- ✓Heads of applied AI research
- ✓Signal processing engineers
- ✓Optimization researchers
- ✓PhD students
Why Attend
Parsimony is the research behind cheaper AI: sparse and low-rank models, compression and structured computation are what cut inference cost and let models run on constrained hardware. A CTO or head of AI infrastructure trying to lower GPU spend can use CPAL to see which efficiency methods have theoretical backing and working systems results, in a four-day single-theme programme. Tokyo also puts it next to the RIKEN AIP and University of Tokyo research groups represented among its chairs and keynotes.
Event Features
- ✓Proceedings Track (published in PMLR)
- ✓Recent Spotlight Track (non-archival)
- ✓Tutorials
- ✓Rising Stars Award
- ✓Keynotes: Yuejie Chi (Yale), Kenji Fukumizu (ISM), Yew-Soon Ong (NTU & A*STAR), Masashi Sugiyama (RIKEN AIP & University of Tokyo)
- ✓Subject areas: Theory and Foundations; Methods and Models; Systems, Data, and Applications
What Makes This Unique
- ★A single-theme machine learning conference on parsimony — sparsity, low rank, symmetry, modularity, compressibility and structured computation — rather than a general AI venue.
- ★Two tracks: archival PMLR proceedings plus a non-archival Recent Spotlight Track for recent work.
- ★Fourth edition, following Tübingen in 2026 (co-organised there by the ELLIS Institute Tübingen and the Max Planck Institute for Intelligent Systems).
- ★General chairs Yi Ma (University of Hong Kong) and Taiji Suzuki (University of Tokyo & RIKEN AIP).
Featured Speakers From
Industries Represented
Pricing Details
Registration fees for CPAL 2027 had not been published as of September 2026.
Organizer
Conference on Parsimony and Learning (CPAL)
cpal.cc/Frequently Asked
- When is CPAL 2027?
- CPAL 2027 takes place March 23–26, 2027 in Tokyo, Japan.
- Where is CPAL 2027 held?
- CPAL 2027 is held in Tokyo, Japan. The event format is in-person.
- What is the CPAL 2027 submission deadline?
- The next CPAL 2027 deadline is proceedings track abstract registration on Nov 23, 2026. Remaining dates: Proceedings track paper deadline — Dec 5, 2026; Tutorial proposal deadline — Dec 10, 2026; Rising Stars Award application deadline — Dec 15, 2026; Reviews released; rebuttal begins — Jan 11, 2027; Tutorial proposal results announced — Jan 14, 2027; Rebuttal period ends — Jan 17, 2027; Recent Spotlight Track submission deadline — Jan 18, 2027; Rising Stars Award notification — Jan 21, 2027; Author–reviewer discussion ends — Jan 22, 2027; Notification to authors (proceedings and spotlight) — Feb 1, 2027; Camera-ready deadline — Feb 12, 2027.
- How much does CPAL 2027 cost?
- CPAL 2027 is paid. Registration fees for CPAL 2027 had not been published as of September 2026.
- Who should attend CPAL 2027?
- CPAL 2027 is aimed at Machine learning researchers, Heads of AI infrastructure and model efficiency, Heads of applied AI research, Signal processing engineers, Optimization researchers, PhD students.
- What topics does CPAL 2027 cover?
- CPAL 2027 covers Sparsity and low-rank methods, Model compression and compressibility, Structured computation, Symmetry and modularity in learning, Optimization, Signal processing, Efficient machine learning.
Sources
This page was written from 5 sources, 2 on domains other than cpal.cc.
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