# CSCI 6220/4030 Randomized Algorithms, Fall 2017

## Overview

Randomized Algorithms are the state of the art in contemporary algorithm design. They are usually simple, sometimes even easy to analyze, and they work well in practice. This course provides an introduction to basic concepts in the design and analysis of randomized algorithms.

## Course Information

A more detailed version of the syllabus is available as an archival pdf.

** Course Text**: Randomized Algorithms, by R. Motwani and P. Ragahavan. We will also cover material from other sources (e.g. papers), that will be linked to on this page

** Grading Criteria**:

- Homeworks, 35%
- In-class Pop Quizzes, 35%
- Final, 30%

Students are expected to have writing supplies on hand in each class to complete the in-class pop quizzes. If you are an athlete or for some other reason are not able to attend each class, make alternative arrangements with the instructor in the first two weeks of the course.

Letter grades will be computed from the semester average. Maximum lower bound cutoffs for A, B, C and D grades are 90%, 80%, 70%, and 60%, respectively. These bounds may be moved lower at the instructors discretion.

## Topics and tentative Schedule

We will be covering most of the chapters in the text, excluding chapters 2,9,13

- Week 1: Randomized Algorithms Overview and Complexity Theory. 1 lecture. Reading: MR95 Chapter 1, except 1.3,1.4
- Week 2: Basic Probability Theory. 1 lecture. Reading: MR95 Appendices B and C
- Week 3: Balls and Bins, Markov and Chebyshev Inequalities, Randomized Selection, Coupon Collector's Problem. 2 lectures. Reading: MR95 Chapter 3
- Week 4: Tail Inequalities and Applications: Chernoff Bounds, Martingales. 2 lectures. Reading: MR95 4.1--4.3 (M), MR95 4.4 (Th)
- TBA

## Homeworks

All assignments must be typed (preferably in LaTeX) and are due at the start of class (defined as the first 10 minutes). ** Late assignments will not be accepted, unless you contact the instructor at least two days before the due date to receive a deferral**. Deferrals will be granted at the instructorâ€™s discretion, of course.

- HW1: Probability Theory Assigned Thursday September 14, due Thursday September 28.
*Start early, and ask questions*

## Supplementary Materials

- TBD