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Pierre Alquier

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2018
[j5]
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  - journals/ml/CottetA18
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Vincent Cottet, Pierre Alquier:
1-Bit matrix completion: PAC-Bayesian analysis of a variational approximation. Machine Learning 107(3): 579-603 (2018)
[j4]
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Pierre Alquier, Benjamin Guedj:
Simpler PAC-Bayesian bounds for hostile data. Machine Learning 107(5): 887-902 (2018)
2017
[c5]
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Pierre Alquier, The Tien Mai, Massimiliano Pontil:
Regret Bounds for Lifelong Learning. AISTATS 2017: 261-269
[i2]
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Pierre Alquier, James Ridgway:
Concentration of tempered posteriors and of their variational approximations. CoRR abs/1706.09293 (2017)
2016
[j3]
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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]
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  - journals/sac/AlquierFEB16
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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]
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Pierre Alquier, The Tien Mai, Massimiliano Pontil:
Regret Bounds for Lifelong Learning. CoRR abs/1610.08628 (2016)
2014
[c4]
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  - conf/nips/RidgwayACL14
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James Ridgway, Pierre Alquier, Nicolas Chopin, Feng Liang:
PAC-Bayesian AUC classification and scoring. NIPS 2014: 658-666
2013
[j1]
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Pierre Alquier, Gérard Biau:
Sparse single-index model. Journal of Machine Learning Research 14(1): 243-280 (2013)
[c3]
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  - conf/alt/Alquier13
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Pierre Alquier:
Bayesian Methods for Low-Rank Matrix Estimation: Short Survey and Theoretical Study. ALT 2013: 309-323
2012
[c2]
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  - conf/dis/AlquierL12
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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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  - conf/alt/Alquier10
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Pierre Alquier:
An Algorithm for Iterative Selection of Blocks of Features. ALT 2010: 35-49

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