## Clustering |

**Some relevant publications:**

- Heller, K.A., Williamson, S., and Ghahramani, Z. (2008) Statistical models for partial
membership. Proceedings of the 25th International Conference on
Machine Learning
**(ICML-2008)**. - Heller, K.A., and Ghahramani, Z. (2007)

A Nonparametric Bayesian Approach to Modeling Overlapping Clusters.

In Eleventh International Conference on Artifical Intelligence and Statistics**(AISTATS-2007)**. San Juan, Puerto Rico. - Azran, A. and Ghahramani, Z. (2006)

A New Approach to Data Driven Clustering.

In International Conference on Machine Learning**(ICML-2006)**. - Azran, A. and Ghahramani, Z. (2006)

Spectral methods for automatic multiscale data clustering.

In IEEE Conference on Computer Vision and Pattern Recognition**(CVPR-2006)**. - Ghahramani, Z. and Heller, K.A. (2006)

Bayesian Sets.

In*Advances in Neural Information Processing Systems 18***(NIPS-2005)**. - Heller, K.A., and Ghahramani, Z. (2005)

Randomized Algorithms for Fast Bayesian Hierarchical Clustering. Statistics and Optimization of Clustering Workshop, Windsor, UK. - Heller, K.A. and Ghahramani, Z. (2005)

Bayesian Hierarchical Clustering, Gatsby Unit Technical Report GCNU-TR 2005-002. [ps] [pdf]

A shorter version was published in the*Twenty-second International Conference on Machine Learning***(ICML-2005)**. [pdf] - Zhu, X., Ghahramani, Z., and Lafferty, J. (2005)

Time-Sensitive Dirichlet Process Mixture Models.

Carnegie Mellon University Technical Report CMU-CALD-05-104. - Zhang, J., Ghahramani, Z. and Yang, Y. (2005)

A Probabilistic Model for Online Document Clustering with Application to Novelty Detection [ps]. [pdf]

In*Advances in Neural Information Processing Systems 17*.**(NIPS-2004)** - Minka, T.P., and Ghahramani, Z. (2003)

Expectation Propagation for Infinite Mixtures.

Technical Report, presented at the*NIPS 2003 Workshop on Nonparametric Bayesian Methods and Infinite Models*.

Talk and abstract at this website. - Ueda, N. and Ghahramani, Z. (2002)

Bayesian model search for mixture models based on optimizing variational bounds

**Neural Networks**15: 1223-1241. -
Ghahramani, Z. and Beal, M.J. (1999)

Variational inference for Bayesian mixtures of factor analysers [pdf] [ps.gz] [abstract]

In**Neural Information Processing Systems 12** - Ueda, N., Nakano,
R., Ghahramani, Z., and Hinton, G. E. (1999)

SMEM Algorithm for Mixture Models. [pdf] [ps]

In**Neural Computation**. - Ghahramani, Z. and Hinton, G.E. (1996)

The EM Algorithm for Mixtures of Factor Analyzers

University of Toronto Technical Report CRG-TR-96-1, 8 pages (short note).

Software written in Matlab.