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.