Spring 2006 - ML Reading Group: Previous Semester Papers

Jan 20
Elias Gyrtodimos and Peter A. Flach "Hierarchical Bayesian Networks: An Approach to Classification and Learning for Structured Data"
Jan 27
Matthew Brand "Nonrigid Embeddings for Dimensionality Reduction"
Feb 10
Lawrence Saul, Kilian Weinburger, Fei Sha, Jihun Ham, Daniel Lee "Spectral Methods for Dimensionality Reduction"
Feb 17
Lawrence Saul, Kilian Weinburger, Fei Sha, Jihun Ham, Daniel Lee (continuing) "Spectral Methods for Dimensionality Reduction"
Feb 24
Markus Breitenbach & Gregory Grudic (continuing) "Clustering Through Ranking On Manifolds"
Mar 3
Cancelled due to CS conference
Mar 10
Pierre Comon "Independent component analysis, A new concept?"
Mar 17
Continuing... Pierre Comon "Independent component analysis, A new concept?"
Mar 31
Cancelled.
April 7
David M. Blei, Thomas L. Griffiths, Michael I. Jordan, Joshua B. Tenenbaum "Hierarchical Topic Models and the Nested Chinese Restaurant Process"
April 14
Thomas L. Griffiths and Zoubin Ghahramani "Infinite Latent Feature Models and the Indian Buffet Process"
April 21
Thomas L. Griffiths and Zoubin Ghahramani "Infinite Latent Feature Models and the Indian Buffet Process"
April 28
Nir Friedman, Moises Goldszmidt and Abraham Wyner "Data Analysis with Bayesian Networks: A Bootstrap Approach"
May 5th
Martijn van Otterlo "A Survey of Reinforcement Learning in Relational Domains"