CSE 290CAdvanced Topics in Machine Learning
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. (Formerly Computer Science 290C.)
Prerequisite(s): CSE 242.
Find a section and add it to your scheduleLive seat counts, time-conflict checks and the walk from your previous class.
When it runs
Winter 2027Open Winter 2027
| Section | Type | When | Where | Instructor | Seats |
|---|---|---|---|---|---|
| 01 | Lecture | Asynchronous | — | R. V. Marinescu | Open 0/30 |
Who teaches it
| Instructor | Rating | Difficulty | Would take again | Reviews |
|---|---|---|---|---|
| Razvan Marinescu | 2.3 / 5 | 2.7 / 5 | 50% | 3 |
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