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A detailed investigation of current machine learning methods, including statistical, connectionist, and symbolic learning. Presents theoretical results for comparing methods and determining what is learnable. Current issues in machine learning research will also be examined. Prerequisite: CSE 5301 or consent of instructor.

Computer Science and Engineering - Graduate Programs

The purpose of the graduate programs in Computer Science (CS) and Computer Engineering (CpE) is to facilitate the student's continued professional and scholarly development. The Master of Science (M.S.) programs are designed to extend the student's knowledge and emphasize a particular area of concentration. The Master of Software Engineering (SwE.) program is designed to provide the student with the opportunity for professional development in the software engineering field. Students who have completed a bachelor's degree in CS, CpE or closely related fields wishing to pursue a doctoral degree may apply for admission in the B.S. to Ph.D. track. The admission requirements to this highly competitive track are the same as those for "advanced admission" (see B.S. to Ph.D. Accelerated Programs). The Doctor of Philosophy (Ph.D.) programs are designed to prepare the student to conduct research and development in an area of concentration.

Electrical Engineering - Graduate Programs

...of CSE 3442 (Embedded Systems I), CSE 5400...5368 EE 6362 EE 6363 EE 6364 EE...

Interdisciplinary Graduate Programs

...graph processing, recommendation systems, and machine learning. CSE 6363. MACHINE LEARNING. 3 Hours. A detailed...