Cap 6: Hidden markov and Maximum Entropy Models D. Jurafsky, J. Martin [2007] [PDF] 

Data Mining (Practical Machine Learning Tools and Techniques) Second Edition. I.Witten, E.Frank [2005]

 New ranking algorithms for parsing and tagging: Kernels over discrete structures, and the voted perceptron. M.Collins [2002] [PDF]

On discriminative vs. generative classifiers: A comparison of logistic regression and Naiv Bayes. A. Ng and M.Jordan [2002]  [PDF]

Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data J.Lafferty, A. McCallum, F.Pereira [2001] [PDF]

Text classification using string kernels. H.Lodhi et al. [2000] [PDF] [508]

Convolution kernels for natural language - M.Collins and N.Duffy [2000] [PDF]

An introduction to Support Vector Machines (and Other Kernel-Based Learning Methods) - N.Cristianinin and J.Shawe-Taylor -  [2000]

 Large margin classification using the perceptron algorithm - Y.Freund and R.E.Schapire [1999] [PDF]

Learning in natural language - D.Roth [1999]

A simple introduction to maximum entropy models for natural language processing - A. Ratnaparkhi [1997] [PDF]

Machine Learning T.Mitchell [1997]

A Maximum Entropy Approach to Natural Language Processing - A.Berger et al - [1996] [PDF]