[ Course Schedule | Midterm and Final | Homework Assignments | Recitations | Resources ]
Instructor: Moses Charikar (email: moses at cs)
Location and time: Monday and Wednesday 1:30 PM - 2:50 PM, CEMEX Auditorium
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Course Description
Worst and average case analysis. Recurrences and asymptotics. Efficient algorithms for sorting, searching, and selection. Data structures: binary search trees, heaps, hash tables. Algorithm design techniques: divide-and-conquer, dynamic programming, greedy algorithms, amortized analysis, randomization. Algorithms for fundamental graph problems: minimum-cost spanning tree, connected components, topological sort, and shortest paths. Possible additional topics: network flow, string searching.
Prerequisites: CS 103 or CS 103B; CS 109 or STATS 116.
Requirements: 7 homework assignments (35%), a midterm (25%), and a final exam (40%).
Teaching Assistants
Will Chen, wic006 at stanford
Ofir Geri (Head TA), ofirgeri at cs
Seth Hildick-Smith, sethjhs at cs
Luke Johnston, lukej at stanford
Anthony Kim, tonye(last-name) at stanford
Sam Kim, samhykim at stanford
Priyanka Nigam, pnigam at stanford
Jimmy Wu, jimmyjwu at stanford
Wilbur Yang, wilbury at cs
Topics and readings for future lectures are tentative and may be changed as the course proceeds. The readings refer to the 3rd edition of CLRS (see Resources below), but older editions should be fine as well.
| Monday | Wednesday | Friday |
| 9/26 Introduction, Why are you here? Read: Ch. 1 Notes (draft) |
9/28 MergeSort, Recurrences, Asymptotics Read: Ch. 2.3, 3 Notes (draft) |
9/30 Homework 1 released |
| 10/3 Integer Multiplication, Solving Recurrences Read: Ch. 4.3-4.5 Dasgupta-Papadimitriou-Vazirani Sec. 2.2 Notes (draft) |
10/5 Median and Selection Read: Ch. 9 Notes (draft) |
10/7 Homework 1 due Homework 2 released |
| 10/10 Quicksort, Probability and Randomized Algorithms Read: Ch. 7, 5 Notes (draft) |
10/12 Sorting Lower Bounds, Counting Sort Read: Ch. 8.1-2 Avrim Blum's Notes on sorting lower bounds Notes on Bucket Sort and Radix Sort (draft) |
10/14 Homework 2 due Homework 3 released |
| 10/17 Binary Search Trees Read: Ch. 12 Notes (draft) |
10/19 Hashing Read: Ch. 11 Notes (draft) |
10/21 Homework 3 due Homework 4 released |
| 10/24 Graphs, DFS, BFS, Dijkstra's Algorithm Read: Ch. 22, 24 Notes (draft) |
10/26 Strongly Connected Components Notes (draft) |
10/28 Homework 4 due |
| 10/31 Midterm |
11/2 Dijkstra's Algorithm, Amortized Analysis, Bellman-Ford Algorithm Read: Ch. 24.1, 24.3 Notes (draft) |
11/4 Homework 5 released |
| 11/7 Dynamic Programming: Floyd-Warshall, Longest Common Subsequence Read: Ch. 25.2, 15.4 Notes (draft) |
11/9 Chain Matrix Multiplication, Knapsack, Independent Set Notes (draft) |
11/11 Homework 5 due Homework 6 released |
| 11/14 Greedy Algorithms Read: Ch. 16 Notes (draft) |
11/16 Minimum Spanning Trees (MST) Read: Ch. 23 Notes (draft) |
11/18 Homework 6 due Homework 7 released |
| 11/21-11/25 Thanksgiving break - no classes |
||
| 11/28 Minimum Cut Notes (draft) |
11/30 Maximum Flow Read: Ch. 26.1-3 Notes (draft) |
12/2 Homework 7 due |
| 12/5 The Wider World of Algorithms |
12/7 Review Session |
12/14 Final Exam |
Midterm: Monday, October 31, in class, 1:30 pm - 2:50 pm
Final: Wednesday, December 14, 3:30 pm - 6:30 pm in 420-040.
Both the midterm and final are closed-book. In the midterm, you are allowed to bring one letter-sized double-sided page of notes. In the final, you are allowed to bring two letter-sized double-sided page of notes.
Practice Midterm
Solutions to the Practice Midterm
Final Exam
Final Exam Solutions
Final Exam - Common Mistakes
Regrade Policy
We hold recitation sections in order to review some of the material and solve additional exercises with the students in smaller groups. The sections are optional but highly recommended. The schedule (including locations) of the recitation sections appears in the office hours calendar. Each section covers the material of the previous week except for Friday sections that cover the material of the same week.
We post here the exercises planned for the recitations.
The main textbook we use is:
Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, Introduction to Algorithms, 3rd Edition, MIT Press
The book is available online through the Stanford library.
We will also occasionally use:
Jon Kleinberg, Éva Tardos, Algorithm Design, Pearson/Addison-Wesley
Sanjoy Dasgupta, Christos Papadimitriou, Umesh Vazirani, Algorithms, McGraw-Hill Education
We strongly recommend typesetting solutions to the homework assignments using LaTeX. LaTeX provides a convenient way to produce high-quality documents and it is the standard used for typesetting computer science papers.
Guide: An introduction to LaTeX can be found here. Other guides can be found at howtoTeX and Wikibooks.
Online environments: If you do not wish to install LaTeX, ShareLaTeX and Overleaf are online environments that compile previews of your documents as you type and allow you to share documents with collaborators (this feature won't be useful in this course, though). As a Stanford student, you get a free Overleaf Pro account.
LyX: LyX is a version of LaTeX with graphical interface.
Finding mathematical symbols: The introduction mentioned above contains a table of mathematical symbols in LaTeX. Alternatively, consider Detexify.
Examples: homework1.tex homework2.tex homework3.tex homework4.tex homework5.tex homework6.tex homework7.tex