Date 
Speaker 
Papers 
Slides 
Dec 1l

Everyone 
NIPS debriefing.
 Francois:

Y. Teh, H. Daume III, D. Roy.
"Bayesian Agglomerative Clustering with Coalescents"

D. Mochihashi, E. Sumita
"The Infinite Markov Model"
 M. Titsias,
"The Infinite GammaPoisson Feature Model"
 Kevin
 "Probabilistic matrix factorization",
Russ Salakhutdiov and Andriy Mnih
 "Using Infer.NET to compare inference algorithms", John Winn
(approx Bayes inf workshop)
 Guillaume
 "A Bayesian Model of Conditioned Perception", by Stocker and
Simoncelli.
 "The tradeoffs of large scale learning" by Léon Bottou
 Hoyt
 "Cluster Stability for Finite Samples"
 "Bayesian Agglomerative Clustering with Coalescents"
 Peter
 "Efficient Principled Learning of Thin Junction Trees" by Anton Chechetka
and Carlos Guestrin
 "New Outer Bounds on the Marginal Polytope" by David Sontag and Tommi
Jaakkola
 Emt
 "Loop Series and Bethe Variational Bounds in Attractive Graphical Models",
E. Sudderth, M. Wainwright, A. Willsky:
 "Bayesian Framework for CrossSituational WordLearning",
Frank, Goodman, Tenenbaum
 "Collapsed Variational Inference for HDP",
Y. Teh, K. Kurihara, M. Welling
 Emt's list
of cool papers

Nov 27

Anthony 
Variational inference in graphical models: The view from the marginal
polytope,
Wainwright and Jordan, 2003.
(Cancelled)

Nov 20

Francois 
On populationbased simulation for
static inference,
Ajay Jasra et al, Statistics and Computing 2007

slides.pdf

Nov 13

Guillaume 
Divergence measures and message passing,
Tom Minka, MSR TR 2005

slides.pdf,
matlab.zip

Nov 6

Emtiyaz 
Building Blocks for Variational Bayesian Learning of Latent Variable Models ,
Tapani Raiko, Harri Valpola, Markus Harva, Juha Karhunen; JMLR, 8(Jan):155201, 2007.

Oct 30

Emtiyaz 
Variational message passing,
J Winn and C Bishop, JMLR 2005

Oct 23

Mark 
A Stochastic Grammar of Images
S.C. Zhu and D. Mumford,
Foundations and Trends in Computer Graphics and Vision, Vol.2, No.4,
pp 259362, 2006

slides.pdf

Oct 16

Anthony 

Intuitive theories as grammars for causal inference
Tenenbaum,
J.B., Griffiths, T. L., and Niyogi, S. (2007). In Gopnik, A., &
Schulz, L. (eds.), Causal learning: Psychology, philosophy, and
computation. Oxford University Press.

Two proposals for causal grammars. Griffiths, T. L. and Tenenbaum,
J. B. (2007). In Gopnik, A., & Schulz, L. (eds.),

Oct 9

No meeting 
.

Oct 2

Francois 
Bayesian nonparametric latent feature models,
Ghahramani, Z., Griffiths, T. L., & Sollich, P. (2007). Bayesian Statistics 8

slides.pdf,
indianBuffet.m

Sep 25

Hendrik 
Hierarchical Dirichlet processes,
Y. W. Teh, M. I. Jordan, M. J.
Beal and D. M. Blei. JASA
101, 15661581, 2006

Sep 18

Emtiyaz 
The Infinite Gaussian Mixture Model, C Rasmussen, NIPS'00
