Calls > Call for papers CAp

 Key dates:
    - Joint Event: 23-26 June 2020
    - Cap papers submission deadline: 26 March 2020 ==> 2 April 2020 
    - Notification to authors for CAp papers: 11 May 2020 ==> 17 May 2020
    - Early bird registration for the conference: 29th May 2020

CAp is an interdisciplinary gathering of researchers at the intersection of machine learning, applied mathematics, and related areas.
The submission website can be found here.
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 the full papers. They present original ideas and provide an opportunity to describe significant work in progress.

We also encourage the submission of recent (2019 or 2020) papers accepted to high level conferences and journals in machine learning. These papers will also be reviewed (lightly) by the program committee. If accepted, they will be presented at the conference but will not appear in any (online) proceedings. Note that, in this particular case, the paper can be submitted in the original conference format (length and style) and the reviews given by the conference/ML journal where it was accepted should be included as the first pages of the submission in addition to a link to the corresponding conference/ML journal web page. The submission of the reviews and the original paper should be merged and submitted into a single PDF file on the easychair website.

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