Calls for Papers > Call for Papers CAp

CAp is France's annual gathering of researchers in machine learning and related fields. Its primary goal is to showcase recently accepted or ongoing research of international quality, giving researchers (in particular PhD students and postdocs) the opportunity to present their work and expand their professional network in a positive and welcoming environment.

The submission website can be found here: TBA

We encourage several kinds of submissions:

• Papers recently accepted (2025 or 2026) at major international conferences of the field (NeurIPS, ICML, ICLR, AISTATS, etc). These papers should be submitted in their original conference format and will be automatically accepted at CAp after a simple verification that the paper's topic fits the conference scope.
   
  • Note: this year we will open a specific track to accommodate papers accepted at ICML 2026 (more details will be added later).
     
• Long original papers which should not exceed 12 pages in CAp format (excluding references and appendices). They will receive at least two reviews.
   
• Short papers that present original ideas and provide an opportunity to describe significant work in progress. They should be up to 8 pages long in CAp format (excluding references and appendices). They will receive at least two reviews.

Submitted papers can be either in English or in French.

There will be no proceedings. The work accepted for presentation will be listed on the website with, optionally, a link to the full papers when provided by the authors.

All accepted papers will have the opportunity to be presented as posters at the conference. A selection of papers will also be invited for oral presentations, either in a CAp-only session or in a joint CAp/RFIAP session (for papers identified as being at the intersection of the two conferences).

Key Dates and Deadlines

• Conference: 6-8 July 2026
• Submission website opens: TBA
• CAp papers submission deadline: March 27, 4pm (Paris time)
• Reviews due: April 24
• Notification to authors for CAp papers: May 7
• Early bird registration deadline: May 31

Topics

The conference and program chairs of CAp 2026 invite those working in areas related to any aspect of machine learning to submit original papers for review. Solicited topics include, but are not limited to:

• Learning theory, models and paradigms:

Active learning
Online learning
Multi-target, multi-task, multi-instance, multi-view and transfer learning
Supervised, unsupervised and semi-supervised learning
Reinforcement learning
Relational learning
Representation learning
Symbolic learning
Bandit algorithms
Matrix and tensor factorization
Optimal Transport for Machine Learning
Grammar induction
Kernel methods
Bayesian methods
Stochastic processes
Ensemble learning and boosting
Graphical models
Gaussian process
Neural networks and deep learning
Learning theory
Game theory

• Optimization and related problems:

Large-scale machine learning and optimization
Optimization algorithms
Distributed optimization
Machine learning and structured data (spatio-temporal data, tree, graph)
Classification with missing values

• Trustworthy machine learning:
  

Fairness
Transparency
Interpretability and Explainability
Privacy and Security
Sustainability
Causality
Alignement and Auditing

• Applications:
  

Health
Social network analysis
Temporal data analysis
Bioinformatic
Data mining
Neuroscience
Natural language processing
Information retrieval
Computer vision
Agroecology