Handouts for EE 290N

The course reader is available from the Copy Central store (2483 Hearst Avenue)

Reference material

Lectures

  • Table of contents (ps file), 8/23/99

    Chapter I: introduction

  • Lecture 1: optimization models (ps file), 8/23/99
  • Lecture 2: linear algebra (ps file), 8/25/99

    Chapter II: convex optimization problems

  • Lecture 3: convex sets (ps file), 8/27/99
  • Lecture 4: convex functions (ps file), 8/30/99
  • Lecture 5: extensions of convexity (ps file), 9/1/99
  • Lecture 6: subgradients and subdifferentials (ps file), 9/8/99
  • Lecture 7: convex optimization problems (ps file), 9/13/99

    Chapter III: convex problems with structure

  • Lecture 8: linear programming (ps file), 9/15/99
  • Lecture 9: convex quadratic programming (ps file), 9/17/99
  • Lecture 10: semidefinite programming (ps file), 9/22/99
  • Lecture 11: geometric programming (ps file), 9/22/99

    Chapter IV: solving convex problems

  • Lecture 12: ellipsoid method (ps file), 9/24/99
  • Lecture 13: duality (ps file), 9/27/99
  • Lecture 14: optimality (ps file), 9/29/99
  • Lecture 15: Smooth unconstrained minimization (part I) (ps file), 10/1/99
  • Lecture 16: Smooth unconstrained minimization (part II) (ps file), 10/4/99
  • Lecture 17: Sequential unconstrained minimization (part I) (ps file), 10/6/99
  • Lecture 18: Sequential unconstrained minimization (part II) (ps file), 10/8/99

    Chapter V: some examples

  • Lecture 19: Geometrical problems (ps file), 10/11/99 and 10/13/99
  • Lecture 20: Data fitting and estimation (ps file), 10/18/99 and 10/20/99
  • Lecture 21: Problems in VLSI design (ps file), 10/22/99 and 10/25/99
  • Lecture 22: Filter design (ps file) (not given)

    Chapter VI: robust optimization

  • Lecture 23: Robust optimization: introduction (ps file) 10/25/99 and 10/27/99
  • Lecture 24: Robust semidefinite programming: part I (ps file) 10/29/99
  • Lecture 25: Uncertainty models (ps file) 11/1/99
  • Lecture 26: Robust semidefinite programming: part II (ps file) 11/3/99

    Chapter VI: ellipsoidal calculus

  • Lecture 27: Linear equations with uncertain data (ps file) 11/8/99 and 11/10/99
  • Lecture 28: Linear equations with structured data (ps file) 11/12/99 and 11/15/99
  • Lecture 29: Identification of uncertain systems (ps file) 11/15/99 and 11/17/99
  • Lecture 30: Set simulation of uncertain systems (ps file) 11/19/99
  • Lecture 31: Robust filtering and control (ps file) 11/22/99

    Chapter VII: conclusions

  • Lecture 32: Conclusions (ps file) 11/24/99

    Homeworks

  • Homework 1 (ps file) , 8/27/99
  • Homework 2 (ps file) , 9/1/99
  • Homework 3 (ps file) , 9/8/99
  • Homework 4 (ps file) , 9/22/99
  • Homework 5 (ps file) , 10/1/99
  • Midterm (ps file) , 10/18/99
  • Homework 6 (ps file) , 11/1/99

    Homework solutions

  • Homework 1 solution (ps file) , 9/1/99
  • Homework 2 solution (ps file) , 9/8/99
  • Homework 3 solution (ps file) , 9/22/99
  • Homework 4 solution (ps file) , 10/8/99
  • Homework 5 solution (ps file) , 10/25/99
  • Midterm solution (ps file) , 10/27/99

    How to use lmitool?

    lmitool is a software software tool that allows to easily develop matlab code solving semidefinite programming problems. It comes with a graphical interface to three different SDP solvers. lmitool is now installed on the instructional network, and works on machines such as quasar.cs. For more information, read this file. You may also visit lmitool's web site.

    Laurent El Ghaoui
    Last modified: October 5, 1999