HUNTERTUTORING

STEM / applied

Optimization for CS · Graduate · CS / Programming

Topics

ML and engineering applications

  • Regularized regression as convex programs
  • ADMM for distributed optimization (intro)
  • Hyperparameter optimization and Bayesian opt (survey)
  • Optimal control and model predictive control (intro)
  • Solver tooling: CVXPY, Gurobi, MOSEK (survey)

Large-scale methods

  • Coordinate descent and proximal algorithms
  • Variance reduction methods (SVRG-style intro)
  • Low-rank matrix completion applications
  • GPU acceleration for optimization workloads
  • Case studies from ML, robotics, and OR

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$1,162 · Optimization for CS · 18 tutoring hrs

Study guides, worksheets, reviews, practice tests, and answer keys for 1 class. 18 tutoring hours (1 hr / week · semester). Bundle discount applied vs buying separately. Pay in full via Zelle.