From diverse datasets to United Nations public good tasks

In personWorkshop
  • Date
    31 May 2024
    Timeframe
    09:15 - 14:15
    Duration
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    Over the last year, we made much progress towards composable systems for working with machine learning’s core asset: data. 

     

    https://data.mlr.press/assets/pdf/v01-5.pdf

    Croissant, a new format for ML ready datasets, has seen the day of light with integrations across Huggingface, Kaggle, OpenML and with loaders for TensorFlow, PyTorch, Jax and Keras, with more than >400k datasets indexed and accessible to date. 

    https://github.com/mlcommons/croissant 

    https://arxiv.org/abs/2403.19546  

     

     

    A burgeoning DMLR (Data-Centric Machine Learning Research) ecosystem has grown, complete with back-to-back workshops at NeurIPS, ICML and ICLR and an ambitious journal 

    https://dmlr.ai/ 

    https://data.mlr.press/ 

     

    In this workshop, we are taking first steps to cross-pollinate ecosystems, matching advanced data-centric methods and infrastructure with high-impact public good expertise. 

     

    On Friday, May 31, we will meet in Geneva to deliberate over a roadmap for one such domain, namely healthcare. 

    The goals of our meeting are threefold: 

    1) Take inventory of the assets we collectively work on in this space 

    2) Align on our vision 

    3) Define a roadmap for the adoption of Croissant Health Extension (or similar format) 

    This will be a no-nonsense-get-things-done workshop meeting. We will meet from 9.30AM to 1.30PM keeping a tight beat with a few coffee breaks inbetween. The schedule is split into two main components. 

    1. A) Round robin inventory presentations: every speaker will give a short 15min summary of their corner of the universe
    2. B) Roadmap discussion: we will define targets for format adoption and dissemination + any serendipitous ideas that come during the discussion

     

     

     

     

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