Fetching the paper…
Reading the bibliography…
We study parameter inference in large-scale latent variable models.
Equation of state calculations by fast computing machines
N. Metropolis, A. Rosenbluth, M. Rosenbluth, A. Teller, and E. Teller · 1953
Earlier work this paper cites.
Monte Carlo sampling methods using Markov chains and their applications
K. Hastings · 1970
Earlier work this paper cites.
Maximum likelihood from incomplete data via the EM algorithm
A. Dempster, N. Laird, and D. Rubin · 1977
Earlier work this paper cites.
Recursive parameter estimation using incomplete data
M. Titterington · 1984
Earlier work this paper cites.
A Monte Carlo implementation of the EM algorithm and the poor man’s data augmentation algorithms
G. Wei and M. Tanner · 1990
Earlier work this paper cites.
Explaining the Gibbs sampler
G. Casella and E. George · 1992
Earlier work this paper cites.
Acceleration of stochastic approximation by averaging
B. Polyak and A. Juditsky · 1992
Earlier work this paper cites.
Online learning and stochastic approximations
L. Bottou · 1998
Earlier work this paper cites.
Theory of point estimation , volume 31
E. Lehmann and G. Casella · 1998
Earlier work this paper cites.
A view of the EM algorithm that justifies incremental, sparse, and other variants
R. Neal and G. Hinton · 1998
Earlier work this paper cites.
Convergence of a stochastic approximation version of the EM algorithm
B. Delyon, M. Lavielle, and E. Moulines · 1999
Earlier work this paper cites.
Estimating a Dirichlet distribution
T. Minka · 2000
Earlier work this paper cites.
Asymptotic Statistics , volume 3
A. Van der Vaart · 2000
Earlier work this paper cites.
Latent Dirichlet allocation
D. Blei, A. Ng, and M. Jordan · 2003
Earlier work this paper cites.
Stochastic approximation and recursive algorithms and applications
H. Kushner and G. Yin · 2003
Earlier work this paper cites.
Finding scientific topics
T. Griffiths and M. Steyvers · 2004
Earlier work this paper cites.
Independent component analysis , volume 46
A. Hyvärinen, J. Karhunen, and E. Oja · 2004
Cited alongside, same era.
Inference in Hidden Markov Models (Springer Series in Statistics)
O. Cappé, E. Moulines, and T. Ryden · 2005
Cited alongside, same era.
Pattern Recognition and Machine Learning
C. Bishop · 2006
Cited alongside, same era.
Hierarchical Dirichlet processes
Y. Teh, M. Jordan, M. Beal, and D. Blei · 2006
Cited alongside, same era.
Topic modeling: beyond bag-of-words
H. Wallach · 2006
Cited alongside, same era.
Natural language processing with Python
S. Bird, E. Klein, and E. Loper · 2009
Cited alongside, same era.
Online EM algorithm for latent data models
Sparse stochastic inference for latent Dirichlet allocation
D. Mimno, M. Hoffman, and D. Blei · 2012
Later among the works it cites.
Machine learning: a probabilistic perspective
K. Murphy · 2012
Later among the works it cites.
Truncation-free online variational inference for Bayesian nonparametric models
C. Wang and D. Blei · 2012
Later among the works it cites.
Non-strongly-convex smooth stochastic approximation with convergence rate O ( 1 / n ) {O}(1/n)
F. Bach and E. Moulines · 2013
Later among the works it cites.
Streaming variational Bayes
T. Broderick, N. Boyd, A. Wibisono, A. Wilson, and M. Jordan · 2013
Later among the works it cites.
Stochastic variational inference
M. Hoffman, D. Blei, C. Wang, and J. Paisley · 2013
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
O. Cappé and E. Moulines · 2009
Cited alongside, same era.
Reading tea leaves: How humans interpret topic models
J. Chang, S. Gerrish, C. Wang, J. Boyd-Graber, and D. Blei · 2009
Cited alongside, same era.
Probabilistic graphical models: principles and techniques
D. Koller and N. Friedman · 2009
Cited alongside, same era.
Online EM for unsupervised models
P. Liang and D. Klein · 2009
Cited alongside, same era.
Evaluation methods for topic models
H. Wallach, I. Murray, R. Salakhutdinov, and D. Mimno · 2009
Cited alongside, same era.
Parallel inference for latent Dirichlet allocation on graphics processing units
F. Yan, N. Xu, and Y. Qi · 2009
Cited alongside, same era.
UCI machine learning repository, 2013
M. Lichman · 2013
Later among the works it cites.
Stochastic gradient Riemannian Langevin dynamics on the probability simplex
S. Patterson and Y. Teh · 2013
Later among the works it cites.
Jointly modeling aspects, ratings and sentiments for movie recommendation (JMARS)
Q. Diao, M. Qiu, C.-Y. Wu, A. J. Smola, J. Jiang, and C. Wang · 2014
Later among the works it cites.
SNAP Datasets: Stanford large network dataset collection
J. Leskovec and A. Krevl · 2014
Later among the works it cites.
Incremental majorization-minimization optimization with application to large-scale machine learning
J. Mairal · 2014
Later among the works it cites.
SAME but different: Fast and high-quality Gibbs parameter estimation
H. Zhao, B. Jiang, and J. Canny · 2014
Later among the works it cites.
Structured stochastic variational inference
M. Hoffman and D. Blei · 2015
Later among the works it cites.
On particle methods for parameter estimation in state-space models
N. Kantas, A. Doucet, S. Singh, J. Maciejowski, and N. Chopin · 2015
Later among the works it cites.
Streaming Gibbs sampling for LDA model
Y. Gao, J. Chen, and J. Zhu · 2016
Closest in time.