Max Welling's Publications in Machine Learning

Y. Zhang, L. Bao, M. Welling, S.H. Yang(2009)
Base Station Localization in Search of Empty Spectrum Spaces for Cognitive Radio Networks
Mobile Ad-hoc and Sensor Networks (MSN) 2009 [pdf]

D. Newman, A. Asuncion, P. Smyth, M. Welling(2009)
Distributed Algorithm for Topic Models
Journal Machine Learning Research 2009 [pdf]

M. Welling(2009)
Herding Dynamic Weights for Partially Observed Random Field Models
UAI 2009 [pdf] [Correction to proof of recurrence, thanks to Olivier Delalleau for pointing out the issue]

M. Welling(2009)
Herding Dynamic Weights to Learn
ICML 2009 [pdf] [Correction to proof of recurrence, thanks to Olivier Delalleau for pointing out the issue]

A. Acuncion, P. Smyth, M. Welling, Y.W. Teh(2009)
On Smoothing and Inference for Topic Models
UAI 2009 [pdf]

Y. Chen and M. Welling(2009)
Bayesian Extreme Components Analysis
IJCAI 2009 [pdf]

S.A. Cole, M. Welling, R.Dioso-Villa, R. Carpenter(2008)
Beyond the Individuality of Fingerprints:
A Measure of Simulated Computer Latent Print Source Attribution Accuracy
Law, Probability and Risk 2008 [pdf]

A. Ascuncion, P. Smyth and M. Welling(2008)
Asynchronous Distributed Learning of Topic Models
NIPS 2008 [pdf]

I. Porteous, A. Ascuncion, D. Newman, A. Ihler, P. Smyth and M. Welling(2008)
Fast Collapsed Gibbs Sampling For Latent Dirichlet Allocation
KDD 2008 [pdf]

Max Welling, Y.W. Teh and B. Kappen(2008)
Hybrid Variational-MCMC Inference in Bayesian Networks
UAI 2008 [pdf]

R. Gomes, M. Welling and P. Perona(2008)
Memory Bounded Inference in Topic Models
ICML 2008 [pdf]

Ian Porteous, Evgeniy Bart and Max Welling (2008)
Multi-HDP: A Nonparametric Bayesian Model for Tensor Factorization
AAAI 2008 [pdf]

Ryan Gomes, Max Welling and Pietro Perona(2008)
Incremental Learning of Nonparametric Bayesian Mixture Models
CVPR 2008 [pdf]

Evgeniy Bart, Ian Porteous, Pietro Perona and Max Welling (2008)
Unsupervised Learning of Visual Taxonomies
CVPR 2008 [pdf]

Max Welling, Chaitanya Chemudugunta and Nathan Sutter (2008)
Deterministic Latent Variable Models and Their Pitfalls
SIAM Conference on Data Mining SDM 2008 [pdf]

Kenichi Kurihara and Max Welling (2008)
Bayesian K-Means as a “Maximization-Expectation” Algorithm
Neural Computation, accepted [pdf]

Max Welling, Ian Porteous and Evgeniy Bart (2007)
Infinite State Bayesian Networks For Structured Domains
NIPS 2007 [pdf]

Dave Newman, Arthur Ascuncion, Padhriac Smyth and Max Welling (2007)
Distributed Inference for Latent Dirichlet Allocation
NIPS 2007 [pdf]

Yee Whye Teh, Kenichi Kurihara and Max Welling (2007)
Collapsed Variational Inference for HDP
NIPS 2007 [pdf]

Max Welling (2007)
Products of Experts
ScholarPedia 2007 [pdf,url]

Alex Holub, Max Welling and Pietro Perona (2007)
Hybrid Generative-Discriminative Object Recognition
International Journal Computer Vision (IJCV) [pdf]

Max Welling and Joseph Lim (2007)
SLEEP: Sensor Location Estimation with Expectation Propagation
ICANN 2007[pdf,June'08, mistake corrected in Alg. Box 3I relative to published version]

Christian Sminchisescu and Max Welling (2007)
Generalized Darting Monte Carlo
AISTATS 2007 [pdf]

Kenichi Kurihara, Max Welling and Yee Whye Teh (2007)
Collapsed Variational Dirichlet Process Mixture Models
IJCAI 2007 [ps,pdf]

Sridevi Parise and Max Welling (2006)
Structure Learning in Markov Random Fields
NIPS 2006 [ps,pdf]

Yee Whye Teh, Dave Newman and Max Welling (2006)
A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation
NIPS 2006 [ps,pdf]

Kenichi Kurihara, Max Welling and Nikos Vlassis (2006)
Accelerated Variational DP mixture Models
NIPS 2006 [ps,pdf]

Max Welling (2006)
Flexible Priors for Infinite Mixture Models
ICML workshop on Nonparametric Baysian methods 2006 [pdf]

Ian Porteous, Alex Ihler, Padhriac Smyth and Max Welling (2006)
Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick-Breaking Representation
UAI 2006 [pdf]

Max Welling and Sridevi Parise (2006)
Bayesian Random Fields: The Bethe-Laplace Approximation
UAI 2006 [pdf]

Peter Gehler, Alex Holub and Max Welling (2006)
The Rate Adapting Poisson (RAP) model for Information Retrieval and Object Recognition.
ICML 2006 [pdf,software]

Alfred Kume and Max Welling (2006)
Maximum-Likelihood Estimation for the Offset Normal Shape Distributions using EM
Submitted [pdf]

Max Welling and Kenichi Kurihara (2005)
Bayesian K-Means as a “Maximization-Expectation” Algorithm
SIAM Conference on Data Mining SDM2006 [pdf,tech-report,software]

Sridevi Parise and Max Welling (2005)
Learning in Markov Random Fields: An Empirical Study
Joint Statistical Meeting JSM2005 [pdf,software]

Geoffrey Hinton, Simon Osindero, Max Welling and Yee Whye Teh (2005)
Unsupervised Discovery of Non-Linear Structure using Contrastive Back-Propagation
Accepted in Cognitive Science 30(4) 2006 [pdf]

Simon Osindero, Max Welling and Geoffrey Hinton (2005)
Topographic Product Models Applied to Natural Scene Statistics
Neural Computation (accepted) [pdf]

Alex Holub, Max Welling and Pietro Perona (2005)
Combining Generative Models and Fisher Kernels for Object Recognition
ICCV 2005 [pdf]

Peter Gehler and max Welling (2005)
Products of “Edge-Perts”
NIPS 2005 [pdf] [software]

Max Welling, Tom Minka and Yee Whye Teh (2005)
Structured Region Graphs: Morphing EP into GBP.
UAI 2005 [ps,pdf] (extended version with proofs)

Max Welling (2005)
Robust Higher Order Statistics
AISTATS 2005 [ps,pdf]

Max Welling (2005)
An Expectation Maximization Algorithm for Inferring Offset-Normal Shape Distributions
AISTATS 2005 [ps,pdf]

Max Welling & Charles Sutton (2005)
Learning in Markov Random Fields with Contrastive Free Energies
AISTATS 2005 [ps,pdf]

Max Welling, Michal Rosen-Zvi & Geoffrey Hinton (2004)
Exponential Family Harmoniums with an Application to Information Retrieval
NIPS 2004 [ps pdf]

Max Welling, Richard Zemel and Geoffrey Hinton (2003)
Probabilistic Sequential Independent Components Analysis
IEEE Transactions on Neural Networks [ps pdf]

Max Welling (2004)
On the Choice of Regions for Generalized Belief Propagation
UAI 2004 [ps pdf]

Max Welling, Michal Rosen-Zvi & Yee Whye Teh (2004)
Approximate Inference by Markov Chains on Union Spaces
ICML 2004 [ps pdf]

Max Welling & Yee Whye Teh (2002)
Linear Response Algorithms for Approximate Inference in Graphical Models
Neural Computation 16 [pdf,Feb.08 typo corrected-thanks to Vicenç Gómez]

Max Welling, Geoffrey Hinton and Andriy Mnih (2003)
Wormholes Improve Contrastive Divergence
NIPS 2003 [ps pdf]

Max Welling, Felix Agakov & Chris Williams (2003)
Extreme Components Analysis
NIPS 2003 [pdf]

Max Welling & Yee Whye Teh (2003)
Linear Response for Approximate Inference
NIPS 2003 [pdf,Feb.08 typo corrected-thanks to Vicenç Gómez]

Max Welling, Richard Zemel and Geoffrey Hinton (2003)
Efficient Parametric Projection Pursuit Density Estimation
UAI 2003 [ps]

Yee Whye Teh, Max Welling, Simon Osindero & Geoffrey Hinton (2003)
Energy-Based Models for Sparse Overcomplete Representations
JMLR [ps]

Yee Whye Teh & Max Welling (2003)
On Improving the Efficiency of the Iterative Proportional Fitting Procedure
AISTATS 2003 [ps]

Max Welling, Richard Zemel and Geoffrey Hinton (2002)
Self-Supervised Boosting
NIPS 2002 [ps]

Max Welling, Geoffrey Hinton and Simon Osindero (2002)
Learning Sparse Topographic Representations with Products of Student-t Distributions
NIPS 2002 [ps]

Max Welling & Yee Whye Teh (2001)
Approximate Inference in Boltzmann Machines
AIJ [ps]

Max Welling & Geoffrey Hinton (2002)
A New Learning Algorithm for Mean Field Boltzmann Machines
ICANN2002, Madrid [ps]

Geoffrey E. Hinton, Max Welling, Yee Whye Teh & Simon K. Osindero (2001)
A New View of ICA
Int. Conf. on Independent Component Analysis and Blind Source Separation, ICA2001, San Diego [ps] 

Yee Whye Teh & Max Welling (2001)
The Unified Propagation and Scaling Algorithm
NIPS2001, Vancouver [ps]

Max Welling & Markus Weber(2001) 
Positive Tensor Factorization 
Pattern Recognition Letters 22 (12), pp. 1255-1261 [ps] 

Max Welling & Yee Whye Teh (2001)
Belief Optimization for Binary Networks: A stable Alternative to Loopy Belief Propagation
UAI2001, Seattle, Washington [ps]

Max Welling & Markus Weber(2001) 
A Constrained EM Algorithm for Independent Component Analysis 
neural computation 13 (3), pp. 677-689  [ps]

Markus Weber, Max Welling & Pietro Perona (2000)
Unsupervised Learning of Models for Recognition 
Proc. 6th Europ. Conf. Comp. Vis., ECCV2000, Dublin [ps]

Markus Weber, Max Welling & Pietro Perona (2000) 
Towards Automatic Discovery of Object Categories 
Proc. IEEE Comp. Soc. Conf. Comp. Vis. and Pat. Rec., CVPR20000, Hilton Head Island [ps]

Markus Weber, Wolfgang Einhauser, Max Welling & Pietro Perona (2000)
Viewpoint-Invariant Learning and Detection of Human Heads 
Proc. 4th Int. Conf. Autom. Face and Gesture Rec., FG2000, Grenoble [ps]

Max Welling & Markus Weber (1999) 
Independent Component Analysis of Incomplete Data 
Proceedings of the 6th Annual Joint Symposium on Neural Computation, JNSC99, Pasadena [ps]

M. Weber, M. Welling & P. Perona (1999)
Unsupervised learning of models for visual object class recognition
Proceedings of the 6th Annual Joint Symposium on Neural Computation, JNSC99, Pasadena [ps]

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Max Welling's Technical Reports and Research Notes in Machine Learning

Max Welling (2008)
Hard Wall Stochastic Control with Hallucination EM and Power EP
Technical Report [pdf]

Alex Holub, Max Welling and Pietro Perona (2005)
Exploiting Unlabelled Data for Hybrid Object Classification
NIPS-2005 workshop in interclass transfer [pdf]

Simon Osindero, Max Welling and Geoffrey Hinton and (2004)
Modeling the Statistics of Natural Images with Topographic Product of Student-t Models
Technical Report [pdf]

Max Welling (2004)
EM Algorithms for Offset-Normal Shape Densities
Techical Report [ps]

Cristian Sminchisescu, Max Welling and Geoffrey Hinton (2003)
Generalized Darting Monte Carlo
Technical Report [pdf]

Max Welling (2001)
Labelling with Loopy Belief Revision
Research Note [ps]

Max Welling & Geoffrey Hinton (2001)
A New Learning Algorithm for Mean Field Boltzmann Machines
Technical Report GCNU TR 2001-002 [ps]

Yee Whye Teh & Max Welling (2001)
Passing and Bouncing Messages for Generalized Inference
Technical Report GCNU TR 2001-001 [ps]

Max Welling (1999)
Robust cumulant expansions for probability density estimation
Technical Report [ps]

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This material is based upon work supported by the National Science Foundation under Grant No. 0447903. and Grant No. 0535278. Any opinions, findings and conclusions or recomendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).

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