[AFDJ03] |
An introduction to MCMC for machine learning |
| by C. Andrieu, N. de Freitas, A. Doucet and M. I. Jordan. |
| Machine Learning, 2003. |
[B98] |
A Tutorial on Support Vector Machines for Pattern Recognition |
| by Chris Burges. |
| KDDM, 1998. |
[BBBCL07] |
Robust Reductions from Ranking to Classification |
| by Nina Balcan, Nikhil Bansal, Alina Beygelzimer, Don Coppersmith, John Langford, and Greg Sorkin. |
| COLT 2007. |
[BDHLZ05] |
Reductions Between Classification Tasks |
| by Alina Beygelzimer, Varsha Dani, Tom Hayes, John Langford and Bianca Zadronzny. |
| ICML, 2005. |
[BKNS04] |
Policy search by dynamic programming |
| by J. Andrew Bagnell, Sham Kakade, Andrew Y. Ng and Jeff Schneider. |
| NIPS 2004. |
[BNJ03] |
Latent Dirichlet allocation |
| by Dave Blei, Andrew Ng and Michael Jordan. |
| JMLR, 2003. (You can ignore Section 5 (Inference and Parameter Estimation)). |
[GE03] |
An Introduction to Variable and Feature Selection |
| by Isabelle Guyon and Andre Elisseeff. |
| JMLR 2003. |
[GS04] |
Finding scientific topics |
| by Tom Griffiths and Mark Steyvers. |
| PNAS, 2004. |
[J04] |
Graphical models |
| by Michael I. Jordan. |
| Statistical Science 2004. |
[KKJ03] |
Exploration in Metric State Spaces |
| by Sham Kakade, Michael Kearns, and John Langford. |
| ICML 2003. |
[KSD06] |
Learning Low-Rank Kernel Matrices |
| by Brian Kulis, Matyas Sustik, Inderjit Dhillon. |
| ICML 2006. |
[L03] |
Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data |
| by Neil Lawrence. |
| NIPS 2003. |
[L05] |
Tutorial on Practical Prediction Theory for Classification |
| by John Langford. |
| JMLR 2005. |
[M03] |
Simplified PAC-Bayesian Margin Bounds |
| by David McAllester. |
| COLT 2003. |
[MPKWJW05] |
Simple Algorithms for Complex Relation Extraction with Applications to Biomedical IE |
| by R. McDonald, F. Pereira, S. Kulick, S. Winters, Y. Jin, and P. White. |
| ACL 2005. |
[N06] |
Linear algebra review and reference |
| by Andrew Ng. |
| Draft tutorial, 2006. |
[NG00] |
PEGASUS: A policy search method for large MDPs and POMDPs |
| by Andrew Y. Ng and Michael I. Jordan. |
| UAI 2000. |
[NMM06] |
Semi-supervised Text Classification Using EM |
| by Kamal Nigam, Andrew McCallum and Tom Mitchell. |
| In Semi-supervised Learning, 2006. |
[PS07] |
Policy Gradient Methods for Robotics |
| by Jan Peters and Stefan Schaal. |
| IROS 2006. |
[Q86] |
Induction of Decision Trees |
| by J.R. Quinlan. |
| MLJ, 1986. |
[S99] |
Perceptron, Winnow, and PAC Learning |
| by R. Servedio. |
| COLT 1999. |
[SB98] |
Reinforcement Learning: An Introduction |
| by Rich Sutton and Andrew Barto. |
| MIT Press, 1998. |
[SM06] |
An Introduction to Condition Random Fields for Relational Learning |
| by Charles Sutton and Andrew McCallum. |
| Book Chapter in Introduction to Statistical Relational Learning, 2006. |
[SWHSL06] |
Spectral methods for dimensionality reduction |
| by L. Saul, K. Weinberger, J. Ham, F. Sha and D. Lee. |
| In "Semisupervised learning" 2006. |
[T08] |
Dirichlet Processes |
| by Yee Whye Teh. |
| Draft tutorial, 2008. |
[TDR07] |
Bayesian Agglomerative Clustering with Coalescents |
| by Yee Whye Teh, Hal Daumé III and Daniel Roy |
| NIPS 2007. |
[WBS06] |
Distance Metric Learning for Large Margin Nearest Neighbor Classification |
| by Kilian Weinberger, John Blitzer and Lawrence Saul. |
| NIPS 2006. |
[WSZS07] |
Graph Laplacian methods for large-scale semidefinite programming, with an application to sensor localization |
| by Kilian Weinberger, Fei Sha, Qihui Zhu and Lawrence Saul. |
| NIPS 2007. |
[ZGL03] |
Semi-supervised learning using Gaussian fields and harmonic functions |
| by Xiaojin Zhu, Zoubin Ghahramani, and John Lafferty. |
| ICML 2003. |