Numerical Optimization (MATH-0228)

Spring 2027 · MATH 0228 · Tufts University · 3 credits · Undergraduate

Advanced numerical optimization with emphasis on modern first- and second-order algorithms, acceleration techniques, large-scale methods, and constrained optimization. Topics include gradient, proximal, mirror, and subgradient methods; heavy-ball and Nesterov acceleration; Newton and quasi-Newton methods; incremental and stochastic gradient methods and randomized coordinate descent; projected gradient descent and interior-point methods. Theoretical foundations and practical applications to real-world problems are emphasized. Programming experience required. Prerequisites: MATH 128, MATH 225, and MATH 226.

Course codes: MATH-0228, MATH 0228, MATH0228, MATH-228, MATH 228, MATH228

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