Daniel P. Robinson
Assistant Professor, Johns Hopkins University, Department of Applied Mathematics and Statistics

Nonlinear Optimization I
EN.550.661 - Fall 2016

General References
J. Nocedal and S. Wright, Numerical Optimization, Second Edition, Springer, 2006. (course textbook) 
A. R. Conn, N.I.M Gould, and Ph. L. Toint, Trust Region Methods, Society for Industrial and Applied Mathematics, Philadelphia, PA, 2000.
R. Fletcher, Practical Methods of Optimization, 2nd Edition, Wiley, Chichester & New York, 1987.
D. P. Bertsekas, Nonlinear Programming, Second Edition, Athena Scientific, Belmont, MA, 1999.
A. Ruszcynski, Nonlinear Optimization, Princeton University press, 2006.
S. Boyd and L. Vandenberghe, Convex Optimization, Cambridge University Press, 2004.

Matlab Help
General TutorialTutorial 
Passing functions as parameters:
    - Download these files ( MYaverage_661.m,  MYaverage_fun_661.m ).
    - Type, for example, MYaverage_661( 'MYaverage_fun_661', 2, 10 ) at the Matlab prompt.
    - Important: note the single quotation marks around MYaverage_fun_661.
Example algorithm output: output_example.txt 

HW1 Due Sept. 21
HW2 Due Oct 3 
HW3 Due Oct 12
HW4 Due Nov 7
HW5 Due Nov 30
HW6 Due Dec 7

Midterm and Final Exams
Midterm: Oct 24 in class
Final: December 15 at 9am

Introduction: lecture00
Background and basics: lecture01   demo01
Convex analysis: lecture02
Newton's Method: lecture03   demo03
Optimality conditions: lecture04
Line-search methods for unconstrained optimization: lecture05
Trust-region methods for unconstrained optimization: lecture06
Least-squares problems: lecture07
Nonlinear equations: lecture08
Convex optimization: lecture09
Stochastic optimization: lecture10
Algorithms that use fixed step sizes: lecture11
Coordinate Minimization: lecture12