[ 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: divideandconquer, dynamic programming, greedy algorithms, amortized analysis, randomization. Algorithms for fundamental graph problems: minimumcost 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 HildickSmith, sethjhs at cs
Luke Johnston, lukej at stanford
Anthony Kim, tonye(lastname) 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. 4.34.5 DasguptaPapadimitriouVazirani Sec. 2.2: [pdf] 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. 8.12 Board transcript 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 Board transcript Notes (draft) 
10/19 Hashing Read: Ch. 11 Board transcript Notes (draft) 
10/21 Homework 3 due Homework 4 released 
10/24 Graphs, DFS, BFS, Dijkstra's Algorithm Read: Ch. 22, 24 Notes (draft) Slides available on Piazza 
10/26 Strongly Connected Components Read: Ch. 24, 6 Notes (draft) Slides available on Piazza 
10/28 Homework 4 due 
10/31 Midterm 
11/2 Dijkstra's Algorithm, Amortized Analysis, BellmanFord Algorithm Read: Ch. 24.1, 24.3 Notes (draft) 
11/4 Homework 5 released 
11/7 Dynamic Programming: FloydWarshall, 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 
11/2111/25 Thanksgiving break  no classes 

11/28 Maximum Flow Read: Ch. 26.13 
11/30 More Maximum Flow, Graph Matchings Read: Ch. 26.23 
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 (Location TBA)
Both the midterm and final are closedbook, but you are allowed to bring one lettersized doublesided page of notes.
Practice Midterm
Solutions to the Practice Midterm
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/AddisonWesley
Sanjoy Dasgupta, Christos Papadimitriou, Umesh Vazirani, Algorithms, McGrawHill Education
We strongly recommend typesetting solutions to the homework assignments using LaTeX. LaTeX provides a convenient way to produce highquality 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