Schedule for Spring 2011

The topics for this semester are Deep Belief Networks, Online Clustering, Manifold learning/feature selection.

Deep Belief Networks

Feb 9 (Ann Irvine)

Feb 16 (Keith Kintzley)

  • Part 2 of the Hinton tutorial
Feb 23 (Ehsan Variani)
  • Geoffrey Hinton and Ruslan Salakhutdinov. Discovering Binary Codes for Documents by Learning Deep Generative Models. Topics in Cognitive Science, 2010.
Mar 2 (Michael Paul)
  • Ryan Prescott Adams, Hanna M. Wallach and Zoubin Ghahramani. “Learning the Structure of Deep, Sparse Graphical Models.” In Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics (AISTATS 2010), Sardinia, Italy, 2010.

Online Clustering

Mar 9 (Michael Carlin)
  • Guha et al. (2003) “Clustering Data Streams: Theory and Practice.” IEEE Trans. Knowledge and Data Engineering.
Mar 16 (Yongjin Park)
  • Canini, Shi, Griffiths. Online Inference of Topics with Latent Dirichlet Allocation. AISTATs, 2009.
Mar 30 (Manaswi Gupta)

  • Beringer and Hullermeier. Online Clustering of Parallel Data Streams. Data & Knowledge Engineering, 2006.
Apr 6 (Sancar Adali)
  • Jian Zhang, Zoubin Ghahramani, Yiming Yang. A Probabilistic Model for Online Document Clustering with Application to Novelty Detection. NIPS, 2004.

Manifold Learning/Feature Selection

Apr 13 (Roberto Tron)
  • Sam T. Roweis, Lawrence K. Saul. “Nonlinear Dimensionality Reduction by Locally Linear Embedding.” Science, 2000
Apr 27 (Delip Rao)
  • Belkin, Niyogi. “Laplacian Eigenmaps for Dimensionality Reduction and Data Representation.” Neural computation, 2003.
May 4 (Bisakha Ray)
  • Shaw, Jebara, “Structure Preserving Embedding”, ICML, 2009.

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