Randomized Algorithms (summer term 2014)

The course is given by Dr. Sabine Storandt. It takes place every Monday and Wednesday from 10:15am until 11:45am in the Hörsaal 03-26 in building 51.

Topics

- Las Vegas & Monte Carlo Algorithms

- Applications for Randomized Algorithms and Data Structures

- Improving Deterministic Bounds via Randomization

- Randomization in Games and AI

- Randomized Online Algorithms

- Probabilistic Method

Script

The complete script of the lecture (including further references) will be made available in the course svn repository.

The current version (last change: 08.07.14) of the script can be viewed here.

(The list of contents may still change during the course of the lecture.)

Exam

The oral exam takes place at 26.08.2014.

Question Time

Please use this Doodle Link to indicate if and when you would like to ask questions about the content of the lecture to prepare for the oral exam.

Dates

1. Preliminaries

28.04. Introduction & Basic Stochastics notes
30.04. Las Vegas and Monte Carlo Algorithms: Analysis and Concentration Bounds, LV & MC for Max 3-SAT notes

2. Randomized Algorithms and Data Structures

05.05. k-Select, Approximative Median and Quick-Sort, Sorting Lower Bound notes
07.05. Sorting Lower Bounds continued, Deterministic & Randomized Skip-Listsnotes
12.05. Universal Hashingnotes
14.05. Exercise. Focus: Deterministic & Randomized Sorting notes example code
19.05. Fingerprinting and Further Hashing Applications, Introduction to Samplingnotes
21.05. VC-dimension of Set Systems & Epsilon-Nets notes
26.05. Exercise + Good Random Samples for Systems with Small VC-dimension and Epsilon-Nets notes
28.05. no lecture
02.06. Good Hitting Set Approximations notes
04.06. Route Planning and Epsilon-Nets notes
16.06. Exercise. Focus: Hitting Sets for Road Networksnotes example code

3. Getting Beyond Deterministic Bounds via Randomization

18.06. The Closest Pair problemnotes
23.06. The Min Cut problemnotes
25.06. Sublinear Algorithmsnotes
30.06. Long Path problems + Exercise (Min Cut and Connected Components)notes example code connected components example code min cut

4. Randomization in AI

02.07. Exercise (Min Cut ctd. and Long Path) + The Cow Path Problem notes
07.07. Robot Navigation in Unknown Terrain: Deterministic Algorithmsnotes
09.07. Robot Navigation in Unknown Terrain: Randomized Algorithmnotes
14.07. Robot Navigation ctd., Competitive Bidding, Exercise: Cows & Robotsnotes

5. Online Algorithms

6. Probabilistic Method