Machine Learning Seminar

Purdue University

 

General Information

Coordinator: Guy Lebanon

We meet and discuss published papers and other research in machine learning and related fields. We try to emphasize active discussion as opposed to regular talks containing a lot of technical details. The participants are strongly encouraged to read the relevant paper or papers before the meeting. If you would like to give a talk, please email the group coordinator. Any topic which is related to machine learning is suitable.

 

Spring 2007

Date Topic Presenter Reading
4/26/07 The information bottleneck Paul Kidwell 1,2
4/19/07 Generalization of PCA to the exponential family Yi Mao 1
4/12/07 Variable and Feature Selection Shivan Tripathi 1
4/6/07 Generalized additive models Jian Zhang 1, 2,
3/30/07 Functional variation and registration Guy Lebanon 1, 2
3/23/07 Functional PCA Balaji Raghavan 1
3/8/07 Handwriting recognition Balaji Raghavan 1,2
3/1/07 Local Regression Guy Lebanon book chapter
2/22/07 Dynamic time warping Guy Lebanon 1, 2
2/15/07 Relational Markov networks Joshua Dillon book chapter (hardcopy). See also 2
2/8/07 SVM discussion (pay special attention to comments) Guy Lebanon 1
2/1/07 concept drift Yang Zhao 1, 2

 

Fall 2006

Date Topic Presenter Reading
12/4/06 seminar cancelled
11/27/06 Classification and Regression using Gaussian processes Jian Zhang 1, 2
11/20/06 Semi-definite programming Guy Lebanon 1
11/13/06 Monte Carlo Methods 2 Guy Lebanon 1
11/6/06 Monte Carlo Methods 1 Guy Lebanon 1
10/30/06 Max margin matrix factorization Jian Zhang 1, 2
10/23/06 Independent component analysis Joshua Dillon 1
10/16/06 Canonical correlation analysis Jian Zhang 1, 2
10/9/06 October break
10/2/06 Max margin networks Yi Mao 1, 2
9/25/06 Kernel PCA Guy Lebanon 1, 2
9/18/06 Sequential document representations and simplicial curves Guy Lebanon uai
9/11/06 Least angle regression Jian Zhang first 39 pages of lars or techRep
8/28/06 Particle filters in robotics Jianying Zhang pFilt

 

Spring 2006

Date

Topic

Presenter

Reading

4/20/06 Spectral clustering Guy Lebanon ncut, spec
4/13/06 A statistical view of boosting Guy Lebanon boost
4/6/06 Lasso regression John Daye lasso
3/30/06 An impossibility theorem for clustering Guy Lebanon clust
3/23/06 Error correcting output codes Guy Lebanon ecoc
3/9/06 Locally linear embedding Guy Lebanon lle
3/2/06 Hubs and authorities Lin Zhu jk
2/23/06 Google and page-rank Guy Lebanon pr1, ant
2/16/06 The MEMM and CRF models for sequence prediction Yi Mao memm, crf
2/9/06 Latent Dirichlet allocation Josh Dillon lda
2/2/06 Local regression and model selection Ben Tyner lr1, lr2
1/26/06 The IBM models for statistical machine translation Guy Lebanon smt
1/19/06 Markov random fields and the Hammersley-Clifford theorem Guy Lebanon mrf1, mrf2