NeurIPS 2019 competition dinner

On going challenge tracks:
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​AUTODL: Automated deep learning. In this challenge series, participants much build learning machines that are trained and tested on new datasets without human intervention whatsoever.
LAP: Looking at People. In this challenge series we are pushing the state-of-the art in computer vision to detect, recognize, and interact with humans.
L2RPN: Learning to run a power network. In this challenge series we expose the community a real world problems of controlling the French electricity transmission grid and investigate whether reinforcement learning can help push the state-of-the-art.

We actively support the development of the Codalab platform. Join the community.
We also support the ChaHub challenge index. Contact us if you want your challenges indexed.

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Mission:

Machine Learning is the science of building hardware or software that can achieve tasks by learning from examples. The examples often come as {input, output} pairs. Given new inputs a trained machine can make predictions of the unknown output.

Examples of machine learning tasks include:

• automatic reading of handwriting
  
• assisted medical diagnosis
  
• automatic text classification (classification of web pages; spam filtering)
  
• financial predictions

We organize challenges to stimulate research in this field. The web sites of past challenges remain open for post-challenge submission as ever-going benchmarks.


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