• Automatic Machine Learning: Until Jan. 2016, $30,000 in prizes donated by Microsoft.
• December: NIPS workshop: CiML 2015. ICCV workshop: LAP 2015.
• See.4C: We have an accepted EU proposal to prepare a large spatio-temporal time series challenge.
• Summer 2015 hackathons: ICML 2015 [watch a video], Petersburg summer school, Stanford bootcamp
• Looking at People 2015: [1] Apparent Age Estimation, [2] Cultural Event Recognition.

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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