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Graduate School
Algorithms
Takashi WATANABE Professor
Department: School of Informatics and Sciences
Class Time:  2016 Spring Thursday 
Recommended for:  School of Information Science 
Course Overview
Course Objectives
This course will give students the ability to understand basic algorithms. It also utilizes concrete problems and demonstrates how to solve them using algorithms and numerical methods.
Key Features
The academic field of algorithms is now increasing. You will learn about some of the representative algorithms and experience how to use them in practices.
Some information technology examinations include problems that involve algorithms. In these cases, you will realize that these problems are similar to those you have learned in the algorithm course.
You can review the course of programming and use the knowledge to apply algorithms to concrete problems. You will also confirm your knowledge of algorithms by tracing the stepbystep processes of problem solving, even though it may be difficult for you to make a program.
During the last five or ten minutes of each class, you will have to opportunity to join in discussion about your questions and/or what you have learned in the class.
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Syllabus
Course Contents
 BNF, regular expressions
 basic algorithms and recursive algorithms
 processing of lists and hash
 processing of graphs
 trees
 sorting
 searching
 information theory
References
No special references are required. Depending upon your request, the teacher will introduce you to some useful materials.
Contents of the lectures
The lectures are given on algorithms that determine problem solving processes in computers. Some of the algorithms are used to demonstrate how to use them in problem solving.
Algorithms Assignments (PDF, 65KB)
Course Schedule
Session  Contents 

1  BNF, regular expressions 
2  basic algorithms and recursive algorithms (review of programming) 
3  processing of lists 
4  processing of hash 
5  processing of graphs (definition of the graph and minimum const spanning tree) 
6  processing of graphs (nondirectional tree, minimum cost directed tree) 
7  trees (definition of tree, traverse and binary tree) 
8  trees (complete binary tree, heap) 
9  trees (processing of complete binary tree) 
10  sorting (classical methods) 
11  sorting (merge sort, quick sort, heap sort) 
12  sorting (other useful sorts) 
13  searching (simple search) 
14  searching (costbased search) 
15  information theory 
Grading
Comprehensive evaluation of reports and the examination
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Class Materials
Lecture Handouts
 1
 BNF, regular expressions (PDF, 64KB)
 2
 basic algorithms and recursive algorithms (review of programming) (PDF, 73KB)
 3
 processing of lists (PDF, 88KB)
 4
 processing of hash (PDF, 102KB)
 5
 processing of graphs (definition of the graph and minimum const spanning tree) (PDF, 137KB)
 6
 processing of graphs (nondirectional tree, minimum cost directed tree) (PDF, 112KB)
 7
 trees (definition of tree, traverse and binary tree) (PDF, 100KB)
 8
 trees (complete binary tree, heap) (PDF, 120KB)
 9
 trees (processing of complete binary tree) (PDF, 123KB)
 10
 sorting (classical methods) (PDF, 83KB)
 11
 sorting (merge sort, quick sort, heap sort) (PDF, 153KB)
 12
 sorting (other useful sorts) (PDF, 82KB)
 13
 searching (simple search) (PDF, 79KB)
 14
 searching (costbased search) (PDF, 102KB)
 15
 information theory (PDF, 124KB)
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Page last updated March 16, 2011
The class contents were most recently updated on the date indicated. Please be aware that there may be some changes between the most recent year and the current page.