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Florence d'Alché-Buc
Florence d'Alché-Buc
Télécom Paris, Institut Polytechnique de Paris
在 telecom-paris.fr 的电子邮件经过验证 - 首页
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引用次数
引用次数
年份
Gene networks inference using dynamic Bayesian networks
BE Perrin, L Ralaivola, A Mazurie, S Bottani, J Mallet, F d’Alche–Buc
Bioinformatics 19 (suppl_2), ii138-ii148, 2003
5782003
Estimating parameters and hidden variables in nonlinear state-space models based on ODEs for biological networks
M. Quach, N Brunel, F d'Alché-Buc
Bioinformatics 23 (23), 3209-3216, 2007
1872007
Support vector machines based on a semantic kernel for text categorization
G Siolas, F d'Alché-Buc
Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural …, 2000
1852000
Incremental support vector machine learning: A local approach
L Ralaivola, F d’Alché-Buc
International conference on artificial neural networks, 322-330, 2001
1562001
Improving reproducibility in machine learning research: a report from the NeurIPS 2019 reproducibility program
J Pineau, P Vincent-Lamarre, K Sinha, V Larivière, A Beygelzimer, ...
Journal of Machine Learning Research 22, 2021
1192021
Semi-supervised marginboost
F d'Alché-Buc, Y Grandvalet, C Ambroise
Advances in neural information processing systems, 553-560, 2001
1172001
Autoregressive models for gene regulatory network inference: Sparsity, stability and causality issues
G Michailidis, F d’Alché-Buc
Mathematical biosciences 246 (2), 326-334, 2013
912013
Semi-supervised penalized output kernel regression for link prediction
C Brouard, F d'Alché-Buc, M Szafranski
Proceedings of the 28th International Conference on Machine Learning (ICML …, 2011
822011
Dynamical modeling with kernels for nonlinear time series prediction
L Ralaivola, F d'Alche-Buc
Advances in neural information processing systems 16, 129, 2004
732004
RAR/RXR binding dynamics distinguish pluripotency from differentiation associated cis-regulatory elements
B Chatagnon, Veber, Morin, Bedo, Triqueneaux, Sémon, Laudet, d'Alché-Buc
Nucleic Acids Research 43 (10), 4833-4854, 2015
722015
Time series filtering, smoothing and learning using the kernel Kalman filter
L Ralaivola, F d'Alché-Buc
Proceedings. 2005 IEEE International Joint Conference on Neural Networks …, 2005
712005
Fast metabolite identification with input output kernel regression
C Brouard, H Shen, K Dührkop, F d'Alché-Buc, S Böcker, J Rousu
Bioinformatics 32 (12), i28-i36, 2016
682016
Kernelizing the output of tree-based methods
P Geurts, L Wehenkel, F d'Alché-Buc
Proceedings of the 23rd international conference on Machine learning, 345-352, 2006
682006
Input output kernel regression: Supervised and semi-supervised structured output prediction with operator-valued kernels
C Brouard, M Szafranski, F d’Alché-Buc
Journal of Machine Learning Research 17 (176), 1-48, 2016
542016
Evolutionary approaches for the reverse-engineering of gene regulatory networks: A study on a biologically realistic dataset
C Auliac, V Frouin, X Gidrol, F d'Alché-Buc
BMC bioinformatics 9 (1), 1-14, 2008
542008
Inferring biological networks with output kernel trees
P Geurts, N Touleimat, M Dutreix, F d'Alché-Buc
BMC bioinformatics 8 (2), 1-12, 2007
542007
Operator-valued kernel-based vector autoregressive models for network inference
N Lim, F d’Alché-Buc, C Auliac, G Michailidis
Machine learning 99 (3), 489-513, 2015
482015
System monitoring the discharging period of the charging/discharging cycles of a rechargeable battery, and host device including a smart battery
JN Patillon, F D'Alche-Buc, JP Nadal
US Patent 5,936,385, 1999
481999
Confidence measures for neural network classifiers
H Zaragoza, F d’Alché-Buc
Proceedings of the Seventh Int. Conf. Information Processing and Management …, 1998
381998
Flexible and context-specific AI explainability: A multidisciplinary approach
V Beaudouin, I Bloch, D Bounie, S Clémençon, F d'Alché-Buc, J Eagan, ...
arXiv preprint arXiv:2003.07703, 2020
372020
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