
B 




2014 
Knowing what we don't know in NCAA Football ratings: Understanding and using structured uncertainty 


B 




2012 
A Bayesian Graphical Model for Adaptive Crowdsourcing and Aptitude Testing 


B 




2012 
Spot Localization using PHY Layer Information 


B 




2011 
Nonconjugate Variational Message Passing for Multinomial and Binary Regression 

E 





2010 
Sparseposterior Gaussian Processes for general likelihoods 


B 


T 

2010 
A Novel Click Model and Its Applications to Online Advertising 



M 



2009 
Probabilistic Programming with Infer.NET 

E 





2009 
Video lectures on Approximate Inference 


B 




2009 
Automating variational inference for statistics and data mining 

E 





2009 
Virtual Vector Machine for Bayesian Online Classification 


B 


T 

2009 
Click Chain Model in Web Search 

E 





2008 
Gates: A graphical notation for mixture models 





T 

2008 
Selection bias in the LETOR datasets 


B 



V 
2008 
Bayesian Color Constancy Revisited 





T 

2008 
SoftRank: Optimising NonSmooth Ranking Metrics 

E 
B 




2007 
TrueSkill Through Time: Revisiting the History of Chess 





T 

2007 
The Smoothed Dirichlet distribution: A new building block for generative topical models 

E 
B 




2006 
TrueSkill: A Bayesian Skill Rating System 




O 


2006 
Local Training and Belief Propagation 

E 





2006 
Windowbased expectation propagation for adaptive signal detection in flatfading channels 


B 

O 

V 
2006 
Cosegmentation of Image Pairs by Histogram Matching  Incorporating a Global Constraint into MRFs 



M 


V 
2006 
Principled Hybrids of Generative and Discriminative Models 



M 



2005 
Discriminative models, not discriminative training 


B 



V 
2005 
Object Categorization by Learned Universal Visual Dictionary 
A Bayesian version of agglomerative information bottleneck. 
E 





2005 
Structured Region Graphs: Morphing EP into GBP 

E 





2005 
Divergence measures and message passing 

E 
B 




2005 
Bayesian Conditional Random Fields 

E 





2004 
Power EP 

E 





2004 
A roadmap to research on EP 

E 
B 




2004 
Predictive Automatic
Relevance Determination by Expectation Propagation 
Preventing overfitting in ARD. 


M 


V 
2004 
Exemplarbased likelihoods using the PDF projection theorem 
How to properly normalize distributions over image features. 


M 

T 
V 
2003 
The `summation hack' as an outlier model 
An explanation of a common trick used in computer vision and text retrieval. 
E 





2003 
Treestructured approximations by expectation
propagation 

E 





2003 
Expectation Propagation for Infinite
Mixtures 


B 



V 
2003 
Bayesian Color
Constancy with NonGaussian Models 

E 





2003 
Expectation Propagation for Signal Detection in Flatfading Channels 



M 



2003 
Building statistical models by visualization 



M 



2003 
Conjugate Analysis of the ConwayMaxwellPoisson Distribution 



M 



2003 
A Useful Distribution for Fitting Discrete Data: Revival of the COMPoisson 



M 



2003 
Computing with the COMPoisson distribution 




O 


2002 
Estimating a Gamma distribution 


B 




2002 
Hessianbased Markov Chain MonteCarlo Algorithms 

E 
B 




2002 
Bayesian inference in dynamic models  an overview 



M 



2002 
Judging significance from error bars 
Something everyone should know how to do, but probably doesn't. 

B 




2002 
Bayesian Spectrum
Estimation of Unevenly Sampled Nonstationary Data 





T 

2002 
Novelty and Redundancy Detection in Adaptive Filtering 

E 



T 

2002 
ExpectationPropagation for the Generative Aspect Model 




O 


2003 
A comparison of numerical optimizers for logistic regression 
Derives and compares eight methods, including iterative scaling. 
E 





2001 
The EP energy function and minimization schemes 

E 





2001 
Expectation Propagation for approximate Bayesian inference 
UAI version of my thesis, with some extra results. 
E 





2001 
A family of algorithms for approximate Bayesian inference 
(PhD thesis work) A powerful generalization of belief propagation. 

B 




2001 
Using lower bounds to approximate integrals 
A new interpretation and generalization of Variational Bayes. 



O 


2000 
Beyond Newton's method 
Custom approximations for fast optimization. 



O 


2000 
Estimating a Dirichlet distribution 
Optimization using Newton, modified Newton, and lower
bounds. 

B 




2000 
Automatic choice of dimensionality for PCA 


B 




2000 
Bayesian model selection 


B 




2000 
Deriving quadrature rules from Gaussian processes 


B 




2000 
Distance measures as prior probabilities 


B 




2000 
Bayesian model averaging is not model combination 


B 




2000 
Empirical Risk Minimization is an incomplete inductive principle 



M 



1999 
Learning How to Learn is Learning With Point Sets 


B 




1999 
Linear regression with errors in both variables:
A proper Bayesian approach 
Total least squares is not optimal. 


M 



1999 
The Dirichlettree
distribution 
The next time you use a Dirichlet, consider a Dirichlettree instead. 





V 
2001 
Document image decoding using iterated complete path search 



M 



1998 
From Hidden Markov Models to Linear Dynamical Systems 


B 




1998 
Bayesian inference, entropy, and the multinomial distribution 
How empirical entropy and empirical mutual information can arise in Bayesian inference. 



O 


1998 
ExpectationMaximization as lower bound maximization 


B 




1998 
Bayesian linear regression 


B 




1998 
Bayesian inference of a uniform distribution 
Bayesian methods succeed where maximumlikelihood does not. 

B 




1998 
Inferring a Gaussian distribution 
Bayes provides a new approach to this ageold problem. 


M 



1998 
Independence Diagrams 
A summary of Bayesian network notation. 

B 




1998 
Pathologies of Orthodox Statistics 



M 



1998 
Nuances of probability
theory 


B 



V 
1998 
An Optimized Interaction Strategy for Bayesian Relevance Feedback 



M 



1997 
Old and New Matrix Algebra Useful for Statistics 






V 
1996 
Modeling user subjectivity in image libraries 






V 
1996 
An Image Database Browser that Learns from User Interaction 






V 
1997 
Interactive Learning using a "Society of Models" 






V 
1995 
Vision Texture for Annotation 
