CS774: References

There will be no textbook for this course. Material available from books, monographs, and publications will form the majority of reference material for the course.

1. [BUB] S. Bubeck, Convex Optimization: Algorithms and Complexity, Foundations and Trends® in Machine Learning, 8(3-4): 231-357, 2015.

2. [HTW] T. Hastie, R. Tibshirani and M. J. Wainwright, Statistical Learning with Sparsity: the Lasso and Generalizations, Chapman and Hall/CRC Press, 2015. [link]

3. [HZN] E. Hazan. Introduction to Online Convex Optimization. Draft, 2015. [link]

4. [SNW] S. Sra, S. Nowozin, and S. Wright (eds). Optimization for Machine Learning, The MIT Press, 2011.

5. [NST] Y. Nesterov, Introductory lectures on convex optimization, Kluwer-Academic, 2003.

6. [BVB] S. Boyd and L. Vandenberghe, Convex Optimization, The Cambridge University Press, 2003. [link]

7. [BRT] D. Bertsekas, Nonlinear programming, Athena Scientific, 1999.

8. Selection of papers from leading conferences and journals in optimization, as well as applied areas such as signal processing, information theory, and machine learning