From clustering to algorithms
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In this talk we firstly provide a rigorous probabilistic proof of the clustering phenomenon taking place in the space of solution of random combinatorial problems. Secondly we will discuss a generalization of the survey propagation equations efficiently exploring the clustered geometry. Finally, we discuss the computational consequences of the possibility of finding single clusters by describing a "physical" lossy compression scheme. Performance are optimized when the number of well separated clusters is maximal in the underlying physical model.

Author: Riccardo Zecchina, International Centre For Theoretical Physics (Ictp)



Tags: VideoLectures.Net, Machine Learning, Clustering, Lectures, Computer Science, Science

Level: advanced Date: September 04, 2008 Votes: 0 User: Dmytro Shteflyuk  Comments:
 
 

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