Probabilistic Inference Group (PIGS) - Archive
Meetings in 2011
29 November: Peter Orchard
15 November: Guido Sanguinetti
1 November: Ioan Stanculescu
We will discuss the following papers:
18 October: Ali Eslami
We will discuss the following papers:
4th October: UAI review
We will review the proceedings of
UAI 2011. If you would like to discuss a paper, please edit this section to include the title together with your initials.
SL:
Pitman-Yor Diffusion Trees - Knowles, Ghahramani
AJS:
Sum Product Networks - Poon, Domingos
NH:
Bregman divergence as general framework to estimate unnormalized statistical models - Gutmann, Hirayama
CKIW:
Conditional Restricted Boltzmann Machines for Structured Output Prediction -- Mnih, Larochelle, Hinton
DR:
Classification of Sets using Restricted Boltzmann Machines -- Louradour, Larochelle
20th September: Matthias Bethge
- Guest lecture by Matthias Bethge.
Tue August 23rd - Shahzad Asif
Tue 9th August - Yichuan Zhang
Tue 26 July - "ICML 2011"
Tue 12 July - Athina Spiliopoulou
We will discuss the following paper:
Tue 28 June - Andrea Ocone
We will discuss the following papers:
Tue 14 June - talk by Michalis Titsias
Title: Sparse Variational Inference for Multi-Task Learning
Tue 17 May - "AISTATS 2011"
Please add your paper nominations together with your initials.
- JK: A. Courville, J. Bergstra, and Y. Bengio: A Spike and Slab Restricted Boltzmann Machine
- GS: Chris Bracegirdle, David Barber: Switch-Reset Models : Exact and Approximate Inference
- AS: Frederik Eaton: A conditional game for comparing approximations
- CW: Jaakko Peltonen, Samuel Kaski: Generative Modeling for Maximizing Precision and Recall in Information Visualization
- AE: I'd actually like to do the Larochelle and Murray paper if Iain isn't interested in doing it himself: H. Larochelle, I. Murray: The Neural Autoregressive Distribution Estimator. (That's fine, IM)
- IM: Two papers on matrix factorization: Lakshminarayanan, Bouchard and Archambeau, Robust Bayesian Matrix Factorisation and Balan, Boyles, Welling, Kim and Park Statistical Optimization of Non-Negative Matrix Factorization
Tue 3 May - Ronald Begg
We will discuss the following paper:
Tue 19 April - Simon Lyons
We will discuss the following papers:
Tue 5 April - Frank Dondelinger
We will discuss the following paper:
Tue 22 March - Grigorios Skolidis
We will discuss the following paper:
Tue 8 March - Botond Cseke
We will discuss the following paper:
Tue 22 February - Chris Williams
We will discuss the following paper:
Tue 8 February - David Reichert
We will discuss the following paper:
- Olivier Breuleux, Yoshua Bengio, and Pascal Vincent, Neural Computation (in press): Quickly Generating Representative Samples from an RBM-Derived Process
If there is time, we will also discuss:
Tue 25 January - Charles Sutton
We will discuss the following paper
Tue 11 January - "NIPS 2010 highlights"
(*) DR: Due to my short notice decision to submit something to ICANN, I probably won't have time to look at the paper, so it's up for grabs.
Leave at bottom of list:
CW: There are lots of other papers I like that I hope someone will choose, e.g. Structured Determinantal Point Processes by Alex Kulesza, Ben Taskar; Tree-Structured Stick Breaking for Hierarchical Data, Ryan Adams, Zoubin Ghahramani, Michael Jordan; The Multidimensional Wisdom of Crowds
Peter Welinder, Steve Branson, Serge Belongie, Pietro Perona; Self-Paced Learning for Latent Variable Models
M. Pawan Kumar, Benjamin Packer, Daphne Koller; Learning Convolutional Feature Hierarchies for Visual Recognition, Kavukcuoglu et al; Divisive Normalization: Justification and Effectiveness as Efficient Coding Transform
Siwei Lyu; Global seismic monitoring as probabilistic inference,Nimar Arora, Stuart Russell, Paul Kidwell, Erik Sudderth (application); Energy Disaggregation via Discriminative Sparse Coding, J. Zico Kolter, Siddharth Batra, Andrew Ng (application)
IM: There are some other papers I could say a sentence or two about: "Tree-Structured Stick Breaking for Hierarchical Data" by Ryan Adams, Zoubin Ghahramani, Michael Jordan; "Global seismic monitoring as probabilistic inference" by Nimar Arora, Stuart Russell, Paul Kidwell, Erik Sudderth; "Label Embedding Trees for Large Multi-Class Tasks" by Samy Bengio, Jason Weston, David Grangier; Comparing "Movement extraction by detecting dynamics switches and repetitions" by Silvia Chiappa, Jan Peters and "Mixture of time-warped trajectory models for movement decoding" by Elaine Corbett, Eric Perreault, Konrad Koerding; "Self-Paced Learning for Latent Variable Models" by M. Pawan Kumar, Benjamin Packer, Daphne Koller.