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MS&E 111: Introduction to Optimization (ENGR 62, MS&E 211)

Formulation and computational analysis of linear, quadratic, and other convex optimization problems. Applications in machine learning, operations, marketing, finance, and economics. Prerequisite: CME 100 or MATH 51.
Terms: Aut | Units: 3-4 | UG Reqs: GER:DB-EngrAppSci, WAY-AQR
Instructors: ; Ye, Y. (PI); Herrscher, J. (TA); Hu, C. (TA); Sun, C. (TA); Zhang, E. (TA); Zhang, X. (TA)

MS&E 111DS: Introduction to Optimization: Data Science (MS&E 211DS)

Formulation and computational analysis of linear, discrete, and other optimization problems. Strong emphasis on data science and machine learning applications, as well as applications in matching and pricing in online markets. Prerequisite: CME 100 or MATH 51.
Terms: Win | Units: 3-4
Instructors: ; Saberi, A. (PI); Archetti, E. (TA); Chung, J. (TA); Miraoui, Y. (TA)

MS&E 111X: Introduction to Optimization (Accelerated) (MS&E 211X)

Optimization theory and modeling. The role of prices, duality, optimality conditions, and algorithms in finding and recognizing solutions. Perspectives: problem formulation, analytical theory, computational methods, and recent applications in engineering, finance, and economics. Theories: finite dimensional derivatives, convexity, optimality, duality, and sensitivity. Methods: simplex and interior-point, gradient, Newton, and barrier. Prerequisite: CME 100 or MATH 51 or equivalent.
Terms: Spr | Units: 3-4 | UG Reqs: WAY-AQR
Instructors: ; Sidford, A. (PI); Archetti, E. (TA); Chung, J. (TA)
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