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       Theory Group

Announcements


• 9/1. Our first lecture will be on Thursday Sep 3 at 9:30AM in CS 1257. We will use Piazza for discussions related to this course. Please follow this link to signup.
• 8/7. Welcome! Please check this space frequently for announcements. More information about the syllabus, instructor, course work, etc. can be found here.


Course Description

Algorithm design and analysis is a fundamental and important part of computer science. This course introduces students to advanced techniques for the design and analysis of algorithms, and explores a variety of applications. Read more ...


Lecture notes & readings

Lecture topics and readings will be posted here over time. Please check frequently. There is no textbook for this course. We will use lecture notes from various sources and read some recent papers.



Lecture	Topic	Suggested readings/references
1 (9/3)	Introduction, reductions, and efficient recursion	Revise chapters 2, 3, 4, 5, 6, 8 from Kleinberg and Tardos
2 (9/8)	Efficient recursion continued	Jeff E.'s notes on Divide & Conquer, Dynamic Programming Shuchi's notes on Divide & Conquer, Dynamic Programming
3 (9/10)	Random variables and events, Testing matrix multiplication	Notes: here, here
4 (9/15)	More on random variables, Analysis of quicksort	Notes on Quicksort
5 (9/17)	Polynomial Identity Testing, Counting via sampling, tail bounds	Notes on PIT, tail bounds
6 (9/22)	Chernoff-Hoeffding bounds, More on sampling	Notes on Chernoff bounds, streaming
7 (9/24)	DNF counting, Load balancing	Notes on DNF counting, Load balancing
8 (9/29)	Power of two random choices	Sinclair's notes
9 (10/1)	Approximation algorithms	Intro and Vertex cover, Set cover, Linear programming
10 (10/6)	Linear programming, LP rounding	Linear Programming, Randomized rounding
11 (10/8)	LP rounding contd., Derandomization	Nick Harvey's notes
12 (10/20)	Derandomization: conditional expectation, pessimistic estimators	Nick Harvey's notes
13 (10/22)	Dimensionality Reduction (Johnson-Linderstrauss)	Nick Harvey's notes, Anupam Gupta's notes
14 (10/27)	Graph sparsification	Nikhil Bansal's notes, Nick Harvey's notes
15 (10/29)	Probabilistic method; Lovasz Local Lemma	Alistair Sinclair's notes
16 (11/3)	Algorithmic (constructive) Local Lemma	Nick Harvey's notes, Tim Roughgarden's notes
17 (11/5)	Online algorithms and competitive analysis, Weighted majority algorithm	Shuchi's notes
18 (11/12)	Hedge, Follow The Perturbed Leader	Bobby Kleinberg's notes, Tim Roughgarden's notes (skip to §3)
19 (11/17)	FTPL continued, LP Duality, Primal-dual analysis	Shuchi's notes
20 (11/19)	Primal Dual analysis continued	Shuchi's notes
21 (11/24)	Online matching	Bobby Kleinberg's notes
22 (12/1)	Online matching continued; Streaming: estimating frequency moments	Tim Roughgarden's notes, Amit Chakrabarti's notes
23 (12/3)	Streaming algorithms




Homeworks


1. HW1       Out: 9/22,      Due: 10/6
2. HW2       Out: 10/20,    Due: 11/3
3. HW3       Out: 11/10,    Due: 11/24
4. Take-home Final    Out: 12/8,    Due: 12/13