Readings (optional, potential, and otherwise)

This list will be updated continuously.

• Charniak, E. (1991). Bayesian networks without tears. AI Magazine, 12, 50-63. http://www.cs.ubc.ca/~murphyk/Bayes/Charniak_91.pdf

• Church, K. and W. Gale, Poor estimates of context are worse than none, Third Darpa Workshop on Speech and Natural Language, Hidden Valley, PA, 1990.

• Clark, A. (2004) "Grammatical Inference and the Argument from the Poverty of the Stimulus", AAAI Spring Symposium on Interdisciplinary Approaches to Language Learning, Stanford, CA. http://www.issco.unige.ch/staff/clark/SS704ClarkA.pdf

• Gale, William A. and Geoffrey Sampson, GoodTuring Frequency Estimation Without Tears, Journal of Quantitative Linguistics, vol. 2, 1995, pp. 217-237. (See also http://www.grsampson.net/RGoodTur.html.)

• Gell-Mann, M. (1994). Information and crude complexity. Chapter 3 in The Quark and the Jaguar (pp. 23-41). http://books.google.com/books?id=l6aCe4zqZ_sC&pg=PA23&lpg=PA23&dq=%22Information+and+crude+complexity.%22&source=web&ots=HiY8fkuCwm&sig=gYWZYllHAxp8_aMNI2lPqvEiv4w&hl=en&sa=X&oi=book_result&resnum=1&ct=result

• Getoor (2006). Lecture notes from Lise Getoor's course on machine learning: http://www.cs.umd.edu/class/spring2006/cmsc726/schedule.html

• Gordon, D. and desJardins, M. (1995). Evaluation and selection of biases in machine learning. Machine Learning Journal 20, pp. 1-17. http://citeseerx.ist.psu.edu/viewdoc/download;jsessionid=7DCFF52ABC4B932F9C8EED68A7F75C44?doi=10.1.1.17.4018&rep=rep1&type=pdf

• Landauer, T. K., Foltz, P. W., & Laham, D. (1998). Introduction to Latent Semantic Analysis. Discourse Processes, 25, 259-284, 1998.

• Landauer T. and Dumais, S., A Solution to Plato's Problem: The Latent Semantic Analysis Theory. Psychological Review 104(2): 211-240, 1997.

• Lappin, S. and S. Shieber (2007), "Machine Learning Theory and Practise as a Source of Insight into Universal Grammar", Journal of Linguistics 43, pp. 293-427 (from http://www.dcs.kcl.ac.uk/staff/lappin/papers/lappin-shieber_learning07.pdf)

• Mitchell, Tom. Machine Learning. McGraw Hill. 1997.

• Pereira, Fernando, Formal grammar and information theory: Together again?<.A>, Philosophical Transactions of the Royal Society, 358, pp. 1239-1253, 2000.

• Pinker, Steven, 1979 "Formal Models of Language Learning", Cognition 7, 217-282, http://wexler.free.fr/library/files/pinker%20(1979)%20formal%20models%20of%20language%20learning.pdf

• Sagan, C. (1979). Can we know the universe? Reflections on a grain of salt. Chapter 2 in Broca's brain (pp. 15-21). http://www.thisviewoflife.org/references/papers/Can%20We%20Know%20the%20Universe%20-%20Sagan1979.pdf

• Zucchini, W. (2000). An introduction to model selection. Journal of Mathematical Psychology, 44, 41-61. http://www-stat.wharton.upenn.edu/~steele/Courses/434/434Context/ModelSelection/Zucchini.pdf