| 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 Gamma-Poisson 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 Cross-Situational Word-Learning",
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 population-based 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):155--201, 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 259-362, 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, 1566-1581, 2006
|
Sep 18
|
Emtiyaz |
The Infinite Gaussian Mixture Model, C Rasmussen, NIPS'00
|