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Convex Analysis

                                                                                                           

Lecturer:   Dr  S. V. N. Vishwanathan
Time:   10 am - 12 noon, Thursdays,  since 31 August, 2006
Venue:   Meeting Room, SML, NICTA
Textbook:  

Convex Analysis and Minimization Algorithms I,

Jean-Baptiste Hiriart-Urruty, and Claude Lemarechal, Springer-Verlag, 1993  (Amazon)

Ref. book:   Convex Analysis, R. T. Rockafellar, Princeton University Press, 1970   (Amazon)
Form:   Reading Group

 Outline: (copied from here)

The course is a foundational overview of convex analysis. It begins by studying real valued convex functions of one real variable and some of their properties including continuity, and closedness. It then studies convex sets, with particular emphasis on the indicator functions of these convex sets. It generalizes the earlier exposition to study convex functions of several variables. The second half of the course focuses on duality and conjugate functions. Throughout the course, geometry will be stressed and plenty of examples will be worked out to clarify concepts.  A brief outline of the course follows:

• Convex functions of one real variable
• Convex sets
• Functions of several variables
• Sub-linearity, support function, sub-differentiability
• Conjugate functions
• Duality

Syllabus:

 No.

 Date

Topic

Scribe

Assignment

(PDF)

1

31 August, 2006

convex sets, affinity, convex operations

scribe 1

solution 1

2

14 September, 2006 (closed) convex hull, closure convexity

scribe 2

solution 2

3

21 September, 2006 relative interior and properties scribe 3 solution 3

4

12 October, 2006 extreme points, exposed faces to be added to be added

5

19 October, 2006 exposed projection (closed convex cone)

to be added

to be added

6

26 October, 2006 relative tangent cones, asymptotic cones

scribe 6

solution 6

7

 

 

   

8

   

 

 
 
     

Other useful resources:

Exercises:

For those who are eager to do more exercises, there is a textbook that can meet your appetite:

Convex Analysis and Optimization, Dimitri P. Bertsekas, Athena Scientific.

The solution of all exercises is available here.

As for original exercises, download the scanned copy here by chapter:       

        ch 1 (13 pages, 45 questions)   2    3    4    5    6    7    8

More notes:

Sometimes, the book says "obviously", "it is easy to see...".  Well, sometimes it is not easy to understand it in an obvious way.  So I will write down the steps as memo.

Counter-examples:

Here I will collect all the interesting counter-examples, which is a very important aspect of learning analysis.

Definitions:

I will put all the definitions together in one file, for easy reference.  A lot of new terminologies!

Theorems and important properties:

I will put all the important theorems, lemmas, corollaries, propositions together in one file, for easy reference.