|
Period
|
Date
|
Topics
|
Chapter
|
Quizzes
|
|
1
|
1/12
|
Motivation; algorithms
|
handout
|
|
|
2
|
1/14
|
The P versus NP problem
|
|
|
|
3
|
1/16
|
Vectors, matrices, norms,
gradients
|
2 and 3
|
|
|
|
1/19
|
Martin Luther King,
Jr. Day---University Holiday
|
|
|
|
4
|
1/21
|
Gradient, directional
derivative, Taylor series
|
5
|
|
|
5
|
1/23
|
Feasible directions,
FONC, SONC
|
6
|
|
|
6
|
1/26
|
SOSC, illustrating
examples
|
|
|
|
7
|
1/28
|
Line search, Fibonacci
method, Golden section search, Newton's method
|
7
|
|
|
8
|
1/30
|
Gradient methods,
steepest descent
|
8
|
|
|
9
|
2/2
|
Convergence of fixed step
size algorithm
|
8
|
|
|
10
|
2/4
|
Order of convergence,
Convergence rate
|
8
|
1
|
|
11
|
2/6
|
Newton's method
|
9
|
|
|
12
|
2/9
|
Conjugate direction
methods
|
10
|
|
|
13
|
2/11
|
Conjugate gradient
algorithm
|
10
Painless_conjugate_gradient
|
|
|
14
|
2/13
|
Quasi-Newton methods
|
11
|
|
|
15
|
2/16
|
Rank one formula
|
11
|
|
|
16
|
2/18
|
DFP and BFGS methods
|
11
|
2
|
|
17
|
2/20
|
Least squares problems,
RLS, parameter identification
|
12
|
|
|
18
|
2/23
|
Genetic algorithms
|
14
Canonical_GA_Convergence
|
|
|
19
|
2/25
|
Review Session
|
|
|
|
20
|
2/25
|
Midterm #1
7:00--8:00pm, EE
170
|
|
|
|
21
|
2/27
|
Analysis of the canonical
algorithm
|
14
|
|
|
22
|
3/2
|
Nelder-Mead simplex algorithm for unconstrained
optimization
|
14
|
|
|
23
|
3/4
|
Linear programs; examples
|
15
|
|
|
24
|
3/6
|
Linear programming; basic
solutions;
|
15
|
|
|
25
|
3/9
|
Linear programming; basic
feasible solutions
|
15
|
|
|
26
|
3/11
|
Simplex algorithm for
solving linear programs
|
16
|
3
|
|
27
|
3/13
|
Two phase algorithm
|
16
|
|
|
|
3/16
|
Spring Break
|
|
|
|
|
3/18
|
Spring Break
|
|
|
|
|
3/20
|
Spring Break
|
|
|
|
28
|
3/23
|
Duality
|
17
|
|
|
29
|
3/25
|
Complementary slackness
|
17
|
|
|
30
|
3/27
|
Optimization problems
with equality constraints, Lagrange condition for scalar equality
constraint
|
19
|
|
|
31
|
3/30
|
Tangent and normal space
|
19
|
|
|
32
|
4/1
|
Review Session
|
|
|
|
33
|
4/1
|
Midterm #2
7:00--8:00pm,
MSEE B012
|
|
|
|
34
|
4/3
|
Problems with equality
constraints---second-order conditions
|
19
|
|
|
35
|
4/6
|
Minimizing quadratics
subject to linear constraints
|
19
|
|
|
36
|
4/8
|
Problems with inequality
constraints,
KKT conditions for
problems with equality and inequality constraints, SONC
|
20
|
4
|
|
4/10
|
Class canceled to make up
for the first evening exam
|
|
|
|
37
|
4/13
|
Second-order conditions
for problems with equality and inequality constraints, examples
|
20
|
|
|
38
|
4/15
|
Convex
functions
|
21
|
|
|
39
|
4/17
|
Convex function
properties
|
21
|
|
|
40
|
4/20
|
Convex optimization
problems
|
21
|
|
|
41
|
4/22
|
SOSC for convex
optimization problems
|
21
|
5
|
|
42
|
4/24
|
Projected gradient
methods
|
22
|
|
|
43
|
4/27
|
Penalty methods
|
22
|
|
|
44
|
4/29
|
Multi-objective
optimization problems
|
23
|
|
|
5/1
|
Class canceled to make up
for the second evening exam
|
|
|
|
45
|
|
Final Exam Presentations
|
|
|