A Theory of Similarity Functions for Learning and Clustering

Machine learning has become a highly successful discipline with applications in many different areas of computer science. A critical advance that has spurred this success has been the development of learning methods using a special type of similarity functions known as kernel functions. These methods have proven very useful in practice for dealing with many different kinds of data and they also have a solid theoretical foundation. In this University of Washington program, Maria-Florina Balcan of
Carnegie Mellon University describes the theory that provides new and simpler explanations.

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Category:

Education

Tags:

• computer
• science
• engineering

[EgyptianPrinceCB]

I took that course .... hard as hell....  huge datasets.. the proofs are still hurting!