- [Slides] How to give a good research talk by Simon Peyton Jones
- [Slides] How to write a great research paper by Simon Peyton Jones
- The Not So Short Introduction to LATEX2e
- MiKTeX Project Page
- Ghostscript, Ghostview and GSview
- Generative and Discriminative Classifiers: Naive Bayes and Logistic Regression by Tom Mitchell
- Naive Bayes Classifier example by Eric Meisner
- A Short Intro to Naive Bayesian Classifiers by Andrew Moore
- CalTech - CS/CNS/EE 155: Probabilistic Graphical Models, Problem Set 2
- Materials for presentation (Homework #1)
- Selective Bayesian Classifiers (SBC) - Langley, P., Sage, S.: Induction of selective Bayesian classifiers. in Proceedings of the Tenth Conference on Uncertainty in Artificial Intelligence, 1994, pp. 339-406.
- ChowLiu algorithm (CL-TAN) - Friedman, N., Greiger, D., Goldszmidt, M.: Bayesian Network Classifiers. Machine Learning 29 (1997) 103-130.
- SuperParent algorithm (SP-TAN) - Keogh, E., Pazzani, M. : Learning augmented bayesian classifiers. Proceedings of Seventh International Workshop on AI and Statistics. (1999) Ft. Lauderdale.
- AVT-NBL - Zhang, J., Kang, D.-K., Silvescu, A., and Honavar, V., "Learning accurate and concise naive Bayes classifiers from attribute value taxonomies and data," Knowledge and Information Systems, 9(2):157-179, March 2006, Springer, ISSN: 0219-1377 (printed version) ISSN: 0219-3116 (electronic version).
- n-gram augmented naive Bayes - Combining Naive Bayes and n -Gram Language Models for Text Classification by Fuchun Peng and Dale Schuurmans
- Decision Trees by Andrew Moore
- L., Hyafil, and R.L., Rivest , "Constructing Optimal Binary Decision Trees is NP-complete", Information Processing Letters, 1976, Vol. 5, No. 1.
- Pedro Domingos: Occam's Two Razors: The Sharp and the Blunt. KDD 1998: 37-43.
- Data Mining Criteria for Tree-Based Regression and Classifiation by Andreas Buja, and Yung-Seop Lee
- Sung-Hyuk Cha and Charles Tappert: A Genetic Algorithm for Constructing Compact Binary Decision Trees, Journal of Pattern Recognition Research, Vol 4, No 1, 2009.
- Lawrence O. Hall, Nitesh Chawla and Kevin W. Bowyer: Combining Decision Trees Learned in Parallel, Distributed Data Mining Workshop at International Conference of Knowledge Discovery and Data Mining, 1998.
- Tapio Elomaa and Matti Kääriäinen: An Analysis of Reduced Error Pruning, Journal of Artificial Intelligence Research 15 (2001) 163-187.
- Pedro Domingos: Occam's Two Razors: The Sharp and the Blunt, KDD 1998.
- Materials for presentation (Homework #2)
- NBTree - Ron Kohavi: Scaling Up the Accuracy of Naive-Bayes Classifiers: a Decision-Tree Hybrid, KDD-96.
- ADTree - Yoav Freund and Llew Mason. The Alternating Decision Tree Algorithm. Proceedings of the 16th International Conference on Machine Learning, pages 124-133 (1999)
- AVT-DTL - Jun Zhang and Vasant Honavar: Learning Decision Tree Classifiers from Attribute Value Taxonomies and Partially Specified Data. In: Proceedings of the Twentieth International Conference on Machine Learning (ICML-03). Washington, DC.
- Recursive Naive Bayes - Kang, D.-K., Silvescu, A., and Honavar, V., "RNBL-MN: A Recursive Naive Bayes Learner for Sequence Classification," Proceedings of the Tenth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006), Singapore, April 9-12, 2006; Lecture Notes in Artificial Intelligence, Vol. 3918, pp. 45-54, 2006, Springer-Verlag.
- Probabilistic Graphical Models, Part One: Graphs and Markov Properties by Christopher M. Bishop
- Probabilistic Graphical Models, Part Two: Inference and Learning by Christopher M. Bishop
- "Chapter 8. Graphical Models". Pattern Recognition and Machine Learning by Christopher M. Bishop
- Bayes Net Learning Tutorial by David Heckerman
- Inference in Bayesian Networks by Scott Davies and Andrew Moore
- Learning Bayesian Networks by Andrew Moore
- NIPS 2001 Tutorial: Learning Bayesian Networks From Data by Nir Friedman and Daphne Koller
- Learning Bayesian Networks Richard E. Neapolitan
- Slides
- Video -
Learning Bayesian Networks
Richard E. Neapolitan
3 videos
- Bayesian Learning by Zoubin Ghahramani
- Video -
Bayesian Learning
Zoubin Ghahramani
2 videos
- Video -
- Materials for presentation (Homework #3)
- The Bayesian structural EM algorithm by Nir Friedman
- Learning Graphical Models with Mercer Kernels by Francis R. Bach and Michael I. Jordan
- Variational Bayesian Learning of Directed Graphical Models with Hidden Variables by Matthew J. Beal and Zoubin Ghahramani
- Learning the Bayesian Network Structure: Dirichlet Prior versus Data by Harald Steck
- Slides
- Video -
Learning the Bayesian Network Structure: Dirichlet Prior versus Data
Harald Steck
- Learning Graphical Model Structure with Sparse Bayesian Factor Models and Process Priors by Ricardo Henao and Ole Winther
- Learning Bayesian networks from postgenomic data with an improved structure MCMC sampling scheme by Dirk Husmeier
