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Sebag, Michele
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1

GAN-based data augmentation for transcriptomics: survey and..:

Lacan, Alice ; Sebag, Michèle ; Hanczar, Blaise
Bioinformatics.  39 (2023)  Supplement_1 - p. i111-i120 , 2023
Link: https://doi.org/10.1093/..
 
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2

From Graphs to DAGs: A Low-Complexity Model and a Scalable ..:

, In: Machine Learning and Knowledge Discovery in Databases; Lecture Notes in Computer Science,
Dong, Shuyu ; Sebag, Michèle - p. 107-122 , 2023
Link: https://doi.org/10.1007/..
 
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3

I2SL: Learn How to Swarm Autonomous Quadrotors Using Iterat..:

, In: Progress in Artificial Intelligence; Lecture Notes in Computer Science,
Shrit, Omar ; Sebag, Michèle - p. 418-432 , 2021
Link: https://doi.org/10.1007/..
 
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4

Cartolabe: A Web-Based Scalable Visualization of Large Docu..:

Caillou, Philippe ; Renault, Jonas ; Fekete, Jean-Daniel..
IEEE Computer Graphics and Applications.  41 (2021)  2 - p. 76-88 , 2021
Link: https://doi.org/10.1109/..
 
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5

Interdisciplinary Research in Artificial Intelligence: Chal..:

Kusters, Remy ; Misevic, Dusan ; Berry, Hugues...
Frontiers in Big Data.  3 (2020)  - p. , 2020
Link: https://doi.org/10.3389/..
 
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6

Agnostic Feature Selection:

, In: Machine Learning and Knowledge Discovery in Databases; Lecture Notes in Computer Science,
Doquet, Guillaume ; Sebag, Michèle - p. 343-358 , 2020
Link: https://doi.org/10.1007/..
 
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7

From Abstract Items to Latent Spaces to Observed Data and B..:

, In: Machine Learning and Knowledge Discovery in Databases; Lecture Notes in Computer Science,
Berger, Victor ; Sebag, Michèle - p. 274-289 , 2020
Link: https://doi.org/10.1007/..
 
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8

Learning Bivariate Functional Causal Models:

, In: Cause Effect Pairs in Machine Learning; The Springer Series on Challenges in Machine Learning,
Goudet, Olivier ; Kalainathan, Diviyan ; Sebag, Michèle. - p. 101-153 , 2019
Link: https://doi.org/10.1007/..
 
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9

Discriminant Learning Machines:

, In: Cause Effect Pairs in Machine Learning; The Springer Series on Challenges in Machine Learning,
Kalainathan, Diviyan ; Goudet, Olivier ; Sebag, Michèle. - p. 155-189 , 2019
Link: https://doi.org/10.1007/..
 
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10

Analysis of the AutoML Challenge Series 2015–2018:

, In: Automated Machine Learning; The Springer Series on Challenges in Machine Learning,
Guyon, Isabelle ; Sun-Hosoya, Lisheng ; Boullé, Marc... - p. 177-219 , 2019
Link: https://doi.org/10.1007/..
 
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11

Algorithm Selector and Prescheduler in the ICON Challenge:

, In: Bioinspired Heuristics for Optimization; Studies in Computational Intelligence,
Gonard, François ; Schoenauer, Marc ; Sebag, Michèle - p. 203-219 , 2018
Link: https://doi.org/10.1007/..
 
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12

Alors: An algorithm recommender system:

Mısır, Mustafa ; Sebag, Michèle
Artificial Intelligence.  244 (2017)  - p. 291-314 , 2017
Link: https://doi.org/10.1016/..
 
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13

Data Stream Clustering With Affinity Propagation:

Zhang, Xiangliang ; Furtlehner, Cyril ; Germain-Renaud, Cecile.
IEEE Transactions on Knowledge and Data Engineering.  26 (2014)  7 - p. 1644-1656 , 2014
Link: https://doi.org/10.1109/..
 
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14

Bi-population CMA-ES agorithms with surrogate models and li..:

, In: Proceedings of the 15th annual conference companion on Genetic and evolutionary computation,
Loshchilov, Ilya ; Schoenauer, Marc ; Sèbag, Michele - p. 1177-1184 , 2013
Link: https://dl.acm.org/doi/1..
 
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15

Sustainable cooperative coevolution with a multi-armed band..:

, In: Proceedings of the 15th annual conference on Genetic and evolutionary computation,
De Rainville, François-Michel ; Sebag, Michèle ; Gagné, Christian.. - p. 1517-1524 , 2013
Link: https://dl.acm.org/doi/1..
 
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