Lab Efficient Algorithms for Selected Problems: Design, Analysis and Implementation

General Information

When Where Start CP Lectures
Lab4Monday, 10:15 - 11:45LBH / E.08October 219Aretz, Röglin

In this lab we will cover all steps of the workflow of designing and implementing algorithms. We will learn about existing methods, implement them, and look for proper data to test them and to compare their performance. We will also learn how to analyze and visualize the outcome of the experiments. Furthermore students are encouraged to develop, implement, and test modifications of the existing methods.

One possible topic will be to study different variants of the k-means algorithm. Further topics will be added if needed. Please feel free to contact us if you are particulary interested in some other domain of (machine learning) algorithms.

We expect your willingness to learn the ropes of the field you selected. If you want to work on clustering techniques, we recommend you to have a first look at the survey by Awasthi and Balcan AB13.

Basic knowledge of Java is mandatory, already having some experience with GNU R will be beneficial.

The preliminary meeting will be on October 21, 10:15. If you plan to attend the lab please let us know in advance by email.

Skript/Folien: Slides of the Preliminary Meeting
Tasklist_01
Tasklist_02
Tasklist_03
Tasklist_04

References

en/lehre/ws1314/lab-efficient-algorithms-selected-problems-design-analysis-and-implementation.txt · Zuletzt geändert: 2014/03/31 12:43 von demir

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