CMPS290C: Advanced Topics in Machine Learning
*****COURSES ARE SUBJECT TO CHANGE*****
In-depth study of current research topics in machine learning. Topics vary from year to year but include multi-class learning with boosting and SUM algorithms, belief nets, independent component analysis, MCMC sampling, and advanced clustering methods. Students read and present research papers; theoretical homework in addition to a research project. Prerequisite(s): course 242. D. Helmbold, M. Warmuth
5 Credits
| Year | Fall | Winter | Spring | Summer |
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| 2017-18 |
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| 2016-17 |
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| 2015-16 |
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| 2014-15 |
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| 2013-14 |
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| 2012-13 |
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| 2011-12 |
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| 2008-09 |
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| 2007-08 |
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| 2006-07 |
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| 2005-06 |
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| 2004-05 |
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| 2003-04 |
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| 2002-03 |
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While the information on this web site is usually the most up to date, in the event of a discrepancy please contact your adviser to confirm which information is correct.