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Semantic ScholarPierre Alquier
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2010 – today
- 2018
[j5]Vincent Cottet, Pierre Alquier:
1-Bit matrix completion: PAC-Bayesian analysis of a variational approximation. Machine Learning 107(3): 579-603 (2018)- [j4]Pierre Alquier, Benjamin Guedj:
Simpler PAC-Bayesian bounds for hostile data. Machine Learning 107(5): 887-902 (2018) - 2017
- [c5]Pierre Alquier, The Tien Mai, Massimiliano Pontil:
Regret Bounds for Lifelong Learning. AISTATS 2017: 261-269 - [i2]Pierre Alquier, James Ridgway:
Concentration of tempered posteriors and of their variational approximations. CoRR abs/1706.09293 (2017) - 2016
- [j3]Pierre Alquier, James Ridgway, Nicolas Chopin:
On the properties of variational approximations of Gibbs posteriors. Journal of Machine Learning Research 17: 239:1-239:41 (2016) - [j2]Pierre Alquier, Nial Friel, Richard G. Everitt, Aidan Boland:
Noisy Monte Carlo: convergence of Markov chains with approximate transition kernels. Statistics and Computing 26(1-2): 29-47 (2016) - [i1]Pierre Alquier, The Tien Mai, Massimiliano Pontil:
Regret Bounds for Lifelong Learning. CoRR abs/1610.08628 (2016) - 2014
- [c4]James Ridgway, Pierre Alquier, Nicolas Chopin, Feng Liang:
PAC-Bayesian AUC classification and scoring. NIPS 2014: 658-666 - 2013
- [j1]Pierre Alquier, Gérard Biau:
Sparse single-index model. Journal of Machine Learning Research 14(1): 243-280 (2013) - [c3]Pierre Alquier:
Bayesian Methods for Low-Rank Matrix Estimation: Short Survey and Theoretical Study. ALT 2013: 309-323 - 2012
- [c2]Pierre Alquier, Xiaoyin Li:
Prediction of Quantiles by Statistical Learning and Application to GDP Forecasting. Discovery Science 2012: 22-36 - 2010
- [c1]
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last updated on 2018-04-08 00:33 CEST by the dblp team