Algorithmic Machine Learning
COM SCI XLC 260B
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This course is part of the UCLA Henry Samueli School of Engineering and Applied Science (HSSEAS) Master of Science in Engineering Online (MSOL) program. It is available only to students pre-approved by HSSEAS. For more information visit msol.ucla.edu.
About this course:
CS 260B Algorithmic Machine Learning (Professor: Meka, R.) Lecture, four hours; outside study, eight hours. In-depth examination of handful of ubiquitous algorithms in machine learning. Covers several classical tools in machine learning but more emphasis on recent advances and developing efficient and provable algorithms for learning tasks. Topics include low-rank approximations, online learning, multiplicative weights framework, mathematical optimization, outlier- robust algorithms, streaming algorithms. S/U or letter grading.