Learning the parts of objects by non-negative matrix factorization, Nature, vol.401, 1999. ,
Non-negative matrix factorization for polyphonic music transcription, 2003 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (IEEE Cat. No.03TH8684), pp.177-180, 2003. ,
DOI : 10.1109/ASPAA.2003.1285860
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.475.7518
Nonnegative Matrix Factorization: An Analytical and Interpretive Tool in Computational Biology, PLoS Computational Biology, vol.14, issue.54, 2008. ,
DOI : 10.1371/journal.pcbi.1000029.t001
Nonnegative Matrix Factorization with the Itakura-Saito Divergence: With Application to Music Analysis, Neural Computation, vol.14, issue.3, pp.793-830, 2009. ,
DOI : 10.1016/j.sigpro.2007.01.024
Distributed nonnegative matrix factorization for web-scale dyadic data analysis on mapreduce, Proceedings of the 19th international conference on World wide web, WWW '10, 2010. ,
DOI : 10.1145/1772690.1772760
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.453.2116
Largescale matrix factorization with distributed stochastic gradient descent, ACM SIGKDD, 2011. ,
DOI : 10.1145/2020408.2020426
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.230.7682
Parallel stochastic gradient algorithms for large-scale matrix completion, Mathematical Programming Computation, vol.8, issue.2, 2013. ,
DOI : 10.1007/s12532-013-0053-8
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.499.9778
Stochastic thermodynamic integration: efficient Bayesian model selection via stochastic gradient MCMC, ICASSP, 2016. ,
Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC, Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD '15, 2015. ,
DOI : 10.1145/2783258.2783373
URL : http://arxiv.org/abs/1503.01596
Bayesian probabilistic matrix factorization using Markov chain Monte Carlo, Proceedings of the 25th international conference on Machine learning, ICML '08, pp.880-887, 2008. ,
DOI : 10.1145/1390156.1390267
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.149.5261
Stochastic gradient Richardson-Romberg Markov chain Monte Carlo, NIPS, 2016. ,
URL : https://hal.archives-ouvertes.fr/hal-01354064
The Theory of Dispersion Models, CRC Monographs on Statistics & Applied Probability, 1997. ,
Learning the beta-divergence in Tweedie compound Poisson matrix factorization models, ICML, pp.1409-1417, 2013. ,
Learning the Information Divergence, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.37, issue.7, pp.1442-1454, 2015. ,
DOI : 10.1109/TPAMI.2014.2366144
URL : http://arxiv.org/abs/1406.1385
Learning mixed divergences in coupled matrix and tensor factorization models, ICASSP, pp.2120-2124, 2015. ,
Optimal weight learning for coupled tensor factorization with mixed divergences, EUSIPCO, pp.1-5, 2013. ,
A Stochastic Approximation Method, The Annals of Mathematical Statistics, vol.22, issue.3, pp.400-407, 1951. ,
DOI : 10.1214/aoms/1177729586
Bayesian learning via Stochastic Gradient Langevin Dynamics, ICML, pp.681-688, 2011. ,
Exponential Convergence of Langevin Distributions and Their Discrete Approximations, Bernoulli, vol.2, issue.4, pp.341-363, 1996. ,
DOI : 10.2307/3318418
Approximation analysis of stochastic gradient Langevin dynamics by using Fokker-Planck equation and Ito process, ICML, pp.982-990, 2014. ,
Consistency and fluctuations for stochastic gradient Langevin dynamics, Journal of Machine Learning Research, vol.17, issue.7, pp.1-33, 2016. ,
On the convergence of stochastic gradient MCMC algorithms with high-order integrators, NIPS, pp.2269-2277, 2015. ,
Bayesian posterior sampling via stochastic gradient Fisher scoring, ICML, 2012. ,
Stochastic gradient Riemannian Langevin dynamics on the probability simplex, NIPS, 2013. ,
Stochastic gradient Hamiltonian Monte Carlo, ICML, 2014. ,
Bayesian sampling using stochastic gradient thermostats, NIPS, pp.3203-3211, 2014. ,
Covariance-controlled adaptive Langevin thermostat for large-scale Bayesian sampling, NIPS, pp.37-45, 2015. ,
A complete recipe for stochastic gradient MCMC, NIPS, pp.2899-2907, 2015. ,
Preconditioned stochastic gradient Langevin dynamics for deep neural networks, AAAI Conference on Artificial Intelligence, 2016. ,
Stochastic quasi-Newton Langevin Monte Carlo, ICML, 2016. ,
Parallel stochastic gradient Markov chain Monte Carlo for matrix factorisation models, 2015. ,
MCMC Using Hamiltonian Dynamics, Handbook of Markov Chain Monte Carlo, 2010. ,
DOI : 10.1201/b10905-6
URL : http://arxiv.org/abs/1206.1901
Parameterisation of a stochastic model for human face identification, Proceedings of 1994 IEEE Workshop on Applications of Computer Vision, pp.138-142, 1994. ,
DOI : 10.1109/ACV.1994.341300
Invariant error metrics for image reconstruction, Applied Optics, vol.36, issue.32, pp.8352-8357, 1997. ,
DOI : 10.1364/AO.36.008352
Efficient Markov chain Monte Carlo inference in composite models with space alternating data augmentation, 2011 IEEE Statistical Signal Processing Workshop (SSP), 2011. ,
DOI : 10.1109/SSP.2011.5967665