Tutorial on Machine Learning Reductions

author: John Langford, Toyota Technological Institute at Chicago
published: Feb. 25, 2007,   recorded: May 2005,   views: 1848
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Description

There are several different classification problems commonly encountered in real world applications such as 'importance weighted classification', 'cost sensitive classification', 'reinforcement learning', 'regression' and others. Many of these problems can be related to each other by simple machines (reductions) that transform problems of one type into problems of another type.

Finding a reduction from your problem to a more common problem allows the reuse of simple learning algorithms to solve relatively complex problems. It also induces an organization on learning problems — problems that can be easily reduced to each other are 'nearby' and problems which can not be so reduced are not close.

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Reviews and comments:

Comment1 Paul, April 5, 2007 at 2:59 a.m.:

bouncy zoomy camera work ruins an otherwise interesting lecture.


Comment2 Alex, July 15, 2008 at 6:33 p.m.:

Thanks for the interesting talk.


Comment3 hamid, February 14, 2009 at 2:25 p.m.:

every thing is satisfactory for someone who have not been thought by good profesors can find this information very
constructive for his trainig

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