Reading List
Bayesian Decision and Graphical Models
[Bishop07] Bishop C, Lasserre J. Generative or discriminative? getting the best of both worlds. In: Bayesian Statistics. Oxford University Press; 2007:3-24.
[Pardo05] Bryan Pardo and William Birmingham. 2005. Modeling form for on-line following of musical performances.
In Proceedings of the 20th national conference on Artificial
intelligence - Volume 2 (AAAI'05), Anthony Cohn (Ed.), Vol. 2. AAAI
Press 1018-1023.
Kernel Methods
[Tikk10] Tikk D, Thomas P, Palaga P, Hakenberg J, Leser U, 2010 A Comprehensive Benchmark of Kernel Methods to Extract Protein–Protein Interactions from Literature. PLoS Comput Biol 6(7): e1000837. doi:10.1371/journal.pcbi.1000837
[Lazebnik06] Svetlana Lazebnik, Cordelia Schmid, and Jean Ponce. 2006. Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories. In Proceedings of the 2006 IEEE Conference on Computer Vision and Pattern Recognition (CVPR '06), Vol. 2, 2169-2178.
Support Vector Learning
[Bleakley07] Bleakley, K. and Biau, G. and Vert, J.P., Supervised reconstruction of biological networks with local models, Bioinformatics, 23(13), pp i57-i65, 2007.
[Ben-Hur05] Ben-Hur, A. and Noble, W.S., Kernel methods for predicting protein--protein interactions, Bioinformatics, 21(1), pp i38-i46, 2005.
[Smola04] A.J. Smola and B. Schölkopf, A tutorial on support vector regression, Statistics and Computing, vol. 14, 2004, pp. 199-222.
Performance Evaluation
[Fawcett06] T. Fawcett, An introduction to ROC analysis, Pattern Recognition Letters, vol. 27, no. 8, pp. 861-874, Jun. 2006.
[Demsar06] J. Demsar, Statistical Comparisons of Classifiers over Multiple Data Sets, Journal of Machine Learning Research, vol. 7, pp. 1-30, 2006.
Unsupervised Learning
[Ding08] C. Ding, X. He, H. D. Simon, and R. Jin, On the Equivalence of Nonnegative Matrix Factorization and K-means - Spectral Clustering, Lawrence Berkeley National Laboratory, 2008.
[Dhillon04] I. S. Dhillon, Y. Guan, and B. Kulis, Kernel k-means , Spectral Clustering and Normalized Cuts,
in Proceedings of the 10th ACM SIGKDD international conference on
Knowledge discovery and data mining - KDD' 04, 2004, pp.
551-556.
Learning on Complex-Structured Data
[Cabestany05] J. Cabestany, A. Prieto, F. Sandoval, J. Weston, B. Scholkopf, and O. Bousquet, Joint Kernel Maps, Proceedings of the 8th International Workshop on Artificial Neural Networks, IWANN 2005, Springer-Verlag, 2005, pp. 176-191.
[Joachims09] Joachims T, Hofmann T, Yue Y, Yu C-N, Predicting structured objects with support vector machines, Communications of the ACM. 2009;52(11)