STANFORD DDA4300/CME307/MS&E311
Optimization in Data Science and Machine Learning
Winter 2021-2023

| Announcements (Check it!) | General Information | Course Outline | Handouts | Assignments |
Announcements

  • Welcome to DDA4300/CME307/MS&E311, 2022-2023!
    Check Course Information for the description of the course, and General Information of the logistics of the course.
    Highlights of this year's topics/applications are Online Pricing and Resource Allocation, Markov Decision Process and Reinforcement Learning, Data Classification via Wasserstein Barycenter, Distributionally Robust Decisioning and Learning, Economic/Game Equilibrium, Financial Techniques and Risk Management, Sparse and Low Rank Regression, Conic Optimization, Steepest Descent Method, Accelerated Descent, BCD methods, SGD methods, ADMM methods, Interior-Point Methods, Lagrangian relaxations, Optimization with random samplings and column generation, and other fast/heuristic Algorithms for nonconvex optimization with certain provable guarantee...

    | Stanford University | MS&E Dept |