Reading List
Bayesian decision theory
[Bishop08] Bishop C. A new framework for machine learning. In: Proceedings of the 2008 IEEE world conference on Computational Intelligence. Springer; 2008:1-24
[Bishop07] Bishop C, Lasserre J. Generative or discriminative? getting the best of both worlds. In: Bayesian Statistics. Oxford University Press; 2007:3-24.
Kernel Methods
[Chen09] Chen Y, Garcia E, Gupta M, Rahimi A, L. Similarity-based classification: Concepts and algorithms. The Journal of Machine Learning Research. 2009;10:747-776.
[Quadrianto10] Quadrianto N, Smola AJ, Song L, Tuytelaars T. Kernelized sorting. IEEE transactions on pattern analysis and machine intelligence. 2010;32(10):1809-21.
Support Vector Learning
[Smola04] A.J. Smola and B. Schölkopf, A tutorial on support vector regression, Statistics and Computing, vol. 14, 2004, pp. 199-222.
[Finley05] Finley T, Joachims T, Supervised clustering with support vector machines, In: Proceedings of the 22nd ACM international conference on Machine learning, 2005, pp 217-224
[Joachims09] Joachims T, Hofmann T, Yue Y, Yu C-N, Predicting structured objects with support vector machines, Communications of the ACM. 2009;52(11)
Performance evaluation
[Domingos99] Domingos, P., MetaCost: a general method for making classifiers cost-sensitive. In Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining, p. 155-164, 1999
[Dietterich98] T.G. Dietterich, Approximate Statistical Tests for Comparing Supervised
Classification Learning Algorithms, Neural Computation, vol. 10,
Oct. 1998, pp. 1895-1923.
Combining Multiple Classifiers
[Viola04] Viola and M.J. Jones, €œRobust Real-Time Face Detection,€ International Journal of Computer Vision, vol. 57, May. 2004, pp. 137-154.
[Breiman01] L. Breiman, €œRandom Forests,€ Machine Learning, vol. 45, 2001, pp. 5-32.
Structured Output Prediction
[Cabestany05] J. Cabestany, A. Prieto, F. Sandoval, J. Weston, B. Scholkopf, and O. Bousquet, €œJoint Kernel Maps,€ Proceedings of the 8th International Workshop on Artificial Neural Networks, IWANN 2005, Springer-Verlag, 2005, pp. 176-191.