Term papers

Each student will write a term paper on one of the topics listed below. The term paper should cover all the key aspects of the topic and contain all the important references related to it.

Suggested Topics

  1. The importance of the Gibbs sampler in Machine-Learning.
  2. Applications of random walks in data mining and information retrieval.
  3. Efficient computation of Pagerank.
  4. The use of random walks for graph clustering.
  5. Applications of Pagerank beyond Web search.
  6. Locality-sensitive hashing and its applications.
  7. Applications of SVD in Machine Learning.
  8. Applications of clustering in Machine Learning.

General guidelines

Imagine a 2nd year computer science undergraduate student is your option. This person has a basic mathematical training, knows programming and has studied data structures, but has yet to study any advanced material. Can you make the topic accessible to this individual? How useful is your term paper for this person trying to learn about this topic? Here are some suggestions to help you along
  1. Read widely about the topic from textbooks and research papers. Make a list of all sources you have read and keep links to them available.
  2. Organize your term paper as follows:
  3. Use latex for your paper (mandatory). Use bibtex for your references.
  4. Make sure each citation is complete and includes author names, full paper title, where published (conference/journal/arXiv/internet), page numbers if known, year. Missing any of these except page numbers is not acceptable.
  5. Finally, once written, re-read and revise. Try to imagine how a person who is reading this for the first time will feel and revise to make it more comprehensible for this person.

Evaluation

All submissions will be through Moodle.
Amitabha Bagchi