CMSC 678: Statistical Learning & Fuzzy Algorithms

The course considers two central problems in modern science and engineering: i) the problem of statistical learning from examples (empirical data) and ii) the problem of embedding existing human knowledge into workable mathematics. Topics include: examples of multivariate functional mapping, basics of classic classification and regression, support vector machines as a learning paradigm based on structural risk minimization, fuzzy logic algorithms, basics of multi-class classification over high dimensional spaces, curve and surface fittings, multivariate function approximation and nonlinear optimization; fuzzy logic systems; crisp and fuzzy sets, linguistic variables, fuzzy set theory; if-then rules, fuzzy interference, fuzzification and defuzzification, neuro-fuzzy paradigms.

Total Credit Hours: 3
Spring 2017
Vojislav Kecman
Instructor Email:

Weekly Live Sessions

Mon Tue Wed Thu Fri Sat
9:30-10:45 AM 9:30-10:45 AM

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Questions? Contact the VCU CGEP Director:

Dr. Gregory Triplett   •   Ph: (804) 828-5387   •