Students are expected to read all the materials in this reading list.
Advice for Graduate Students
How to be a good graduate student, by Marie des Jardin.
Guide for graduate
students, by Kevin Murphy.
What are the characteristics of the successful graduate student?, from Cornell Univ.
Advice on designing scientific posters, by Colin Purrington.
Writing guidelines for engineering and science students, by Michael Alley.
Tips for english writing, from IEICE.
Selected Journals and Conferences
Microsoft Academic Search: Rank lists in Computer Science.
Conference-I: ICDM, ICPR, ICML, SMC, SIGKDD, CIKM, PAKDD.
Conference-II: ISMB, CBMS, EMBC, BIBE.
Conference-III: MM, ISMIR, ICASSP, ICME, HRI.
Data Mining Web Sites
KDnuggets: Data Mining Community's Top Resource [Home]
KDDCUP: SIGKDD Annual Data Mining and Knowledge Discovery Competition [Home]
UCI Machine Learning Repository [Home]
WEKA Machine Learning Project [Home]
The R Project for Statistical Computing [Home]
MATLAB Bioinformatics Toolbox [Home]
by Richard O. Duda, Peter E. Hart, David G. Stork (Wiley-Interscience)
Linear Algebra and Its Applications
by David C. Lay (Addison Wesley)
Princples of Data Mining
by David J. Hand, Heikki Mannila, Padhraic Smyth (The MIT Press)
Data Mining: Pratical Machine Learning Tools and Techniques
by Ian H. Witten, Eibe Frank (Morgan Kaufmann)
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
by Trevor Hastie,
Robert Tibshirani, Jerome Friedman (Springer)
by Thomas Mitchell (McGraw Hill Higher Education)
by Sergios Theodoridis, Konstantinos Koutroumbas (Academic Press)
C4.5: Programs for Machine Learning
by J. Ross Quilan (Morgan Kaufmann)
Artificial Intelligence: A Mordern Approach
by Stuart Russell, Peter Norvig (Prentice Hall)
Introduction to Algorithms
by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein (The MIT Press)