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CMPS 290c S07: Final Project: MCMC Algorithms for solving Multitask Co-Leraning Problem

By Ricardo Menchaca-mendez

Abstract

This project presents the di ¢ culties in bounding the mixing time of the Markov chain presented in [1] for solving the multitask co-learning problem. In particular I show why the technics of canonical paths and coupling can not be directly applied. Then I propose an alternative markov chain that approximate the notion of co-learning for which a bounding in the mixing time is possible. The upper bound, unfortunately, is not polynomial in m-the number of ’good ’ learners. To try to cope with that I give possible alternatives that might allow a bounding that depend only polynomialy in m.

Year: 2007
OAI identifier: oai:CiteSeerX.psu:10.1.1.192.5638
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