Course Information (Spring 2015)
Instructor: | Prof. Faye Briggs, DH 2062 | Graduate TAs: | Deepak Majeti, DH 2069 |
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Lectures: | Keck 107 | Lecture times: | F 11:00 am - 11:50am |
Schedule for Student Presentations
Note: The slides and related material for each topic will be provided. Hence, do not hesitate about the workload if you like a topic not in your domain.
Topic | Student Name | Date | Presentation | |
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1 | Distributed file systems and map-reduce as a tool for creating parallel algorithms that succeed on very large amounts of data | 2/6/2015 | ||
2 | Similarity search, including the key techniques of min-hashing and locality sensitive hashing | 2/13/2015 | ||
3 | Data-stream processing and specialized algorithms for dealing with data that arrives so fast it must be processed immediately or lost | 2/20/2015 | ||
4 | The technology of search engines, including Google’s Page Rank, link-spam detection, and the hubs-and-authorities approach | 2/27/2015 | ||
5 | Frequent-itemset mining, including association rules, market-baskets, the A-Priori Algorithm and its improvements | 2/6/2015 | ||
6 | Algorithms for clustering very large, high-dimensional datasets | 3/13/2015 | ||
7 | Two key problems for Web applications: managing advertising and recommendation systems | 3/20/2015 | ||
8 | Algorithms for analyzing and mining the structure of very large graphs, especially social-network graphs | 3/27/2015 | ||
9 | Techniques for obtaining the important properties of a large dataset by dimensionality reduction, including singular-value decomposition and latent semantic indexing | |||
10 |