CAp2020: Conférence d'Apprentissage Campus de Tohannic Vannes, France, June 24-26, 2020 |
Conference website | https://cap-rfiap2020.sciencesconf.org/ |
Submission link | https://easychair.org/conferences/?conf=cap20200 |
Submission deadline | March 26, 2020 |
CAp is an interdisciplinary gathering of researchers at the intersection of machine learning, applied mathematics, and related areas.
We encourage the submission of recent papers accepted to high level conferences and journals in Machine Learning.
Submitted papers can be either in English or in French and we encourage two types of submissions:
- Full research papers on the theme of machine learning theory and its applications should not exceed 10 pages in CAp double-column format (including references and figures). A suitable LaTeX template for CAp is available *here*.
- Short papers can be up to four to 6 pages using the same format as Full papers. They present original ideas and provide an opportunity to describe significant work in progress.
Some accepted papers will be presented in a *long* (20 minutes) oral presentation and all the accepted papers will be given the opportunity to be presented as a spotlight (3 minutes) and as a poster at the conference. These presentations are an opportunity to have constructing and rigorous feedbacks, as well as to establish contacts with members of the french machine learning community. PhD Students are particularly welcome and encouraged to submit papers. Contributions will be freely distributed on the conference website, subject to approval by the authors.
The conference and program chairs of CAp 2020 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
Grammar induction
Kernel methods
Bayesian methods
Spectral methods
Stochastic processes
Ensemble learning and boosting
Graphical models
Gaussian process
Neural networks and deep learning
Learning theory
Game theory
Optimization et 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
Applications:
Social network analysis
Temporal data analysis
Bioinformatic
Data mining
Neuroscience
Natural language processing
Information retrieval
Computer vision
Key dates:
- Joint Event: 23-26 June 2020
- Cap papers submission deadline: 26 March 2020
- Notification to authors for CAp papers: 11 May 2020
- Early bird registration for the conference: 29th May 2020