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UAI 2014 - Submission Statistics

Primary Subject Areas

Submit Accept
Learning 120 40
Nonparametric Bayes 12 6
Structure Learning 11 4
Regression 10 5
Probabilistic Generative Models 8 2
Active Learning 7 3
Classification 7 2
Clustering 7 1
Online and Anytime Learning 7 3
Reinforcement Learning 7 2
Unsupervised 7 2
Parameter Estimation 6 2
Semi-Supervised Learning 6 2
General 4 1
Ranking 4 2
Recommender Systems 4 1
Learning Theory 3 1
Deep Learning 2 0
Relational Learning 2 1
Scalability 2 0
Structured Prediction 2 0
Other 2 0
   
Principles 24 9
Causality 7 3
Decision Theory 5 2
Statistical Theory 3 1
Information Theory 2 0
Cognitive Models 1 0
Game Theory 1 1
Probability Theory 1 0
Other 4 2
   
Representation 10 3
Dempster-Shafer 3 1
Fuzzy Logic 2 0
Non-Probabilistic Frameworks 3 1
Probabilistic 2 1
   
   
Submit Accept
Algorithms 63 23
Approximate Inference 20 8
Optimization 15 6
Exact Inference 9 2
MCMC methods 8 4
Belief Propagation 4 1
Distributed and Parallel 2 0
Heuristics 2 0
Graph Theory 1 1
Other 2 1
   
Applications 41 8
Planning and Control 8 4
Vision 5 0
Privacy and Security 4 1
Robotics 4 0
Social Network Analysis 4 0
Text and Web Data 4 0
Education 2 0
Medicine 2 0
Big Data 2 1
Biology 1 1
Decision Support 1 0
Diagnosis and Reliability 1 0
Sensor Data 1 1
Sustainability and Climate 1 0
Other 1 0
   
Methodology 32 10
Topic Models 7 1
Bayesian Networks 6 1
Markov Decision Processes 6 2
Probabilistic Programming 3 0
Bayesian Methods 3 1
Undirected Graphical Models 2 2
Calibration 1 1
Elicitation 1 1
Directed Graphical Models 1 0
Dynamic Bayesian Networks 1 1
Mixed Graphical Models 1 0

Total: 292

Topics Detected From Abstracts

(Groups of words that tend to co-occur)
inference bayesian networks network variational Submit Accept
inference bayesian networks network variational 109 33
dimensional active discovering projections amounts 36 11
graphs graph node edges undirected 26 5
neighbor sensitive environment methodology input 20 8
budget regret dimension high subset 17 6
structures structure collections layers effect 16 2
     
models model process gp gaussian    
process models model gaussian graphical 113 41
nonparametric modelling processes issue components 27 11
rule combination trained training inputs 32 14
discovery logical expert features accuracy 24 7
gp sparse inducing support regression 14 6
communication dependence gibbs sampler cancer 7 2
points point trajectories kernel kernels 5 5
computer vision experiment 5 0
     
monte chain carlo markov mcmc  
chain markov mcmc 15 3
monte carlo 19 5
     
variables random programming transformation branch    
variables programming discrete probabilistic variable 38 16
map settings linear affect locality 26 10
random fields mrfs clustered sizes 15 5
transformation branch sum recognition product 12 4
     
estimator deterministic estimators tracking covariate    
significant computational leibler kl improvements 22 10
approximate computation standard assigning euclidean 19 7
deterministic sample covariate tracking reference 18 5
convergence gradient rate descent 15 10
estimator estimators consistency 7 5
     
action actions agent mdps state    
action actions agent mdps state 19 4
decision pomdp tree pomdps diagrams 7 4
transition contributions cooperative observational maps 7 0
   
rewards delta reward epsilon preferences  
uncertainty uncertain objects sensor images 36 11
examples generalized soft box hmm 24 9
preferences correlation restriction correlated polynomial 20 8
confidence matching abstract biological sequence 19 6
expected spatial aid return field 17 4
optimality bounded access inherent chance 15 5
experimental handling margin querying boundary 9 1
rewards delta reward 7 2
     
data sets synthetic unlabeled classifiers    
data sets synthetic infer missing 121 38
learning machine learn crucial learns 92 34
classification unlabeled classifiers classifier labeled 23 8
word words semantic analogy concepts 9 1
bn performances units effects 6 0
     
clusters topic cluster clustering document    
risk mutual derive information link 20 8
connected independently pca subsets dependencies 18 10
clusters cluster clustering 15 4
topic document topics documents corpus 14 5
groups group 7 1
dirichlet allocation latent 6 4
     
matrix personalized mechanism factorization items    
filtering motion particle collaborative overlapping 18 1
matrix factorization 14 1
rank square norm matrices alternating 7 3
personalized items user 4 0
mechanism strategies response queries cope 4 0
manifold manifolds 4 2
     
function objective optimization belief functions    
function objective optimization functions optimal 57 19
lower bound upper bounds maximizing 40 17
maximum pairwise log minimization constant 36 15
robust important noise structural essential 32 5
family simulation simulations estimation parameter 28 9
belief propagation energy 12 5
global maximal optimum overfitting 11 2
formulation scalability convex update requirements 13 7
detection series switching financial stock 13 3
labels label 9 5

 

The topics summarize common word combinations in the abstracts. They are detected using latent tree analysis, which also gives the topic groupings and group labels. Each topic corresponds to a soft collection of abstracts, and is characterized using the words that are most important for distinguishing the collection from the rest of the corpus. The counts are calculated via hard assignment.

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