Fall 2015 Course Descriptions

COMP 236-01 Computational Learning Theory

R. Khardon
TR 10:30-11:45, Lane Hall 100A
D+ Block

Probabilistic and adversarial models of machine learning. Development and analysis of machine learning principles and algorithms, their computational complexity, data complexity and convergence properties. Computational and cryptographic limitations on algorithms for machine learning. Core results and recent developments in this field.

Prerequisite: Prerequisites: COMP 160; EE 104 or MATH 162; COMP 170 recommended but not required. Or permission of instructor.

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