Algorithmic challenges
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Algorithmic challenges
Written by Sue Gee   
Thursday, 19 May 2011

If you are up for a challenge then TunedIT might have one for you, complete with a reward.  It aims to use crowd sourcing to solve algorithmic problems for a profit.


 

In the most recent addition to the list, a prize of $45,000 is being offered for the best pattern recognition algorithm for the identification of substances from electromagnetic signatures.

This challenge is one of three current contests underway at TunedIT an online laboratory dedicated to development of intelligent algorithms through crowdsourcing.

The other two offer more modest rewards. One that ends next week for most efficient intelligent heuristic for the problem of job allocation under constraints has two prizes of $1000 and $500. The other is a data mining challenge with a prize fund of 5,500 Euros (four awards) that started a month ago.

The latest challenge, Materials Identification Based on Measurements of Passively Emitted Electromagnetic Radiation has been issued by FIND Technologies, a Canadian company that owns novel sensor technology for measuring electromagnetic signatures of materials. FIND already possesses an algorithm for this task, which achieves accuracy of 79% but is looking for a 95% threshold.

Realizing that its expertise in data mining and advanced intelligent algorithms is limited it decided to take advantage of crowdsourcing, which appealed because of easy access to large pool of talented programmers and experienced specialists. 

Launching a contest with TunedIT means that several hundred professionals will approach the task, each of them with different methods and ideas, and holds out the prospect that of finding the best possible solution.

This contest will last until November 30, 2011 or until the 95% threshold is achieved and is open to all programmers, statistician or data scientist who can register to participate at http://tunedit.org/challenge/material-classification.

 

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Last Updated ( Thursday, 19 May 2011 )
 
 

   
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