Reading list for students
This page provides links and references to useful reading material in computer science, research methodology, and writing. Within computer science, emphasis is put on machine learning and related areas of research. The page is primilariy aimed at providing Master and Research students with links to introductory, foundational, and inspirational work. Please notify me if you find any broken links or other errors.
Seminal publications concerning machine learning
Note: I use bold text within parentheses to describe, at least from my pespective, one main contribution of each publication.
Breiman, L., Friedman, J. H., Olshen, R. A., Stone, C. J. (1984). Classification and Regression Trees, Chapman & Hall / CRC. (Introduction of the CART decision tree learner)
Literature about writing
Williams, J. M. (2006). The Craft of Argument.
Williams, J. M. (2010). Style: The Basics of Clarity and Grace.
Zinsser, W. (2001). On Writing Well: The Classic Guide to Writing.
Zobel, J. (2014). Writing for Computer Science. Third edition. Springer.
Literature about research methodology
Demeyer, S. (2011). Research Methods in Computer Science. IEEE International Conference on Software Maintenance.
Langley, P. W.; Kibler, D. (1991). The Experimental Study of Machine Learning.
Ramesh, V.; Glass, R. L.; Vessey, I. (2004). Research in Computer Science: An Empirical Study. Systems and Software, 70:165-176.
Blogs and web-based tutorials
- Amaral et al., "About Computing Science Research Methodology"
- Ayash, "Research Methodologies in Computer Science and Information Systems"
- Comer, "How to Write a Dissertation"
- Demeyer, "Research Methods in Computer Science"
- Dodig-Crnkovic, "Scientific Methods in Computer Science"
- Goebel and Plagemann, "Research / Scientific Methods in Computer Science"
- Ryerson University, "Research Methods for Computer Science"
- Smith and Smith, "Empirical Research Methods in Computer Science"