Coursebooks 2016-2017

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Advanced algorithms

CS-450

Lecturer(s) :

Svensson Ola Nils Anders

Language:

English

Summary

A first graduate course in algorithms, this course assumes minimal background, but moves rapidly. The objective is to learn the main techniques of algorithm analysis and design, while building a repertory of basic algorithmic solutions to problems in many domains.

Content

Algorithm analysis techniques: worst-case and amortized, average-case, randomized, competitive, approximation. Basic algorithm design techniques: greedy, iterative, incremental, divide-and-conquer, dynamic programming, randomization, linear programming.  Examples from graph theory, linear algebra, geometry, operations research, and finance.

Keywords

See content.

Learning Prerequisites

Required courses

An undergraduate course in Discrete Structures / Discrete Mathematics, covering formal notation (sets, propositional logic, quantifiers), proof methods (derivation, contradiction, induction), enumeration of choices and other basic combinatorial techniques, graphs and simple results on graphs (cycles, paths, spanning trees, cliques, coloring, etc.).

Recommended courses

An undergraduate course in Data Structures and Algorithms.

An undergraduate course in Probability and Statistics.

Important concepts to start the course

Basic data structures (arrays, lists, stacks, queues,trees) and algorithms (binary search; sorting; graph connectivity); basic discrete mathematics (proof methods, induction, enumeration and counting, graphs); elementary probability and statistics (random variables, distributions, independence, conditional probabilities); data abstraction.

Learning Outcomes

By the end of the course, the student must be able to:

Teaching methods

Ex cathedra lecture, reading

Assessment methods

 

 

Supervision

Office hours Yes
Assistants Yes
Forum Yes
Others For details, see the course web page.

Resources

Bibliography

See web page for the course.

Ressources en bibliothèque
Notes/Handbook

Class notes and references for the running semester will be provided as needed within a few days after each lecture.

Websites

In the programs

Reference week

 MoTuWeThFr
8-9 INJ218  INR219
9-10   
10-11    INR219
11-12     
12-13     
13-14   INJ218 
14-15    
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22     
 
      Lecture
      Exercise, TP
      Project, other

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  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German