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


Nonlinear Optimization I
EN.553.761 - Fall 2017

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 

Homework
 
HW1 Due Sept. 21
HW2 Due Oct 05
HW3 Due Oct 12
HW4 Due Nov 7
HW5 Due Nov 16
HW6 Due Dec 5

 
Midterm and Final Exams
 
Midterm: Oct 17 in classroom
Final: December 19 at 2pm in classroom (review sheet)

Lectures
 
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
Coordinate Minimization: lecture09
Algorithms with convergence to second-order points: lecture10