The University of Texas at Austin 3 credits Computer Science
Analyze recent developments on the role of machine learning in designing algorithms from the dual viewpoints of tailoring algorithm design to exploit the availability of data as well as tailoring learning to optimize for algorithm performance. Computer Science 388D and 395T (Topic: Data-Driven Algorithm Design) may not both be counted. Three hours a week for one semester Pre/Corequisites: Graduate standing and knowledge of undergraduate algorithms and complexity, and at least one graduate course in theoretical computer science. Prior knowledge in randomized algorithms and machine learning.
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