We will update this page with additional resources. We encourage you to share other relevant resources that you have found useful and we will add to this list.

Text books

There is no prescribed textbook for the class.

Readings for the course are either available on the course website or will be provided as handouts in the class. Some additional resources are listed below for background and extra reading:

  1. Noah Smith, Linguistic structure prediction, 2011. This book is available online if you are in the university network.

  2. Sebastian Nowozin and Christoph H. Lampert, Structured Learning and Prediction in Computer Vision, 2011. (Based on a tutorial at CVPR, 2011. The material can also be accessed here).

  3. Christopher D. Manning and Hinrich Schutze, Foundations of Statistical Natural Language Processing, 1999.

  4. Daniel Jurafsky and James H. Martin, Speech and Language Processing, 2008 (second edition).

  5. Trevor Hastie, Robert Tibshirani, Jerome Friedman, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2009 (second edition).

  6. Stephen Boyd and Lieven Vandenberghe, Convex Optimization, 2004. (This book covers convex optimization in general and is a very useful resource for understanding learning algorithms that minimize loss)

  7. Natural Language Processing papers at the ACL anthology.

  8. Proceedings of machine learning and learning theory papers at JMLR: Workshop and Conference Proceedings.