| How to assess step-size adaptation mechanisms in randomised search N Hansen, A Atamna, A Auger International Conference on Parallel Problem Solving from Nature, 60-69, 2014 | 25 | 2014 |
| Augmented Lagrangian constraint handling for CMA-ES—case of a single linear constraint A Atamna, A Auger, N Hansen International Conference on Parallel Problem Solving from Nature, 181-191, 2016 | 24 | 2016 |
| Benchmarking ipop-cma-es-tpa and ipop-cma-es-msr on the bbob noiseless testbed A Atamna Proceedings of the Companion Publication of the 2015 Annual Conference on …, 2015 | 24 | 2015 |
| Linearly convergent evolution strategies via augmented Lagrangian constraint handling A Atamna, A Auger, N Hansen Proceedings of the 14th ACM/SIGEVO Conference on Foundations of Genetic …, 2017 | 18 | 2017 |
| COmparing continuous optimizers: numbbo/COCO on Github (2019) N Hansen, D Brockhoff, O Mersmann, T Tusar, D Tusar, OA ElHara, ... URL https://doi. org/10.5281/zenodo 2594848, 0 | 11 | |
| COmparing Continuous Optimizers: numbbo/COCO on Github, March 2019 N Hansen, D Brockhoff, O Mersmann, T Tusar, D Tusar, OA ElHara, ... URL https://doi. org/10 5281, 2019 | 9 | 2019 |
| Analysis of linear convergence of a (1+ 1)-ES with augmented lagrangian constraint handling A Atamna, A Auger, N Hansen Proceedings of the Genetic and Evolutionary Computation Conference 2016, 213-220, 2016 | 7 | 2016 |
| SPI-GCN: a simple permutation-invariant graph convolutional network A Atamna, N Sokolovska, JC Crivello | 5 | 2019 |
| A Principled Approach to Analyze Expressiveness and Accuracy of Graph Neural Networks. A Atamna, N Sokolovska, JC Crivello IDA, 27-39, 2020 | 4 | 2020 |
| A methodology for building scalable test problems for continuous constrained optimization P Sampaio, N Hansen, D Brockhoff, A Auger, A Atamna Book of Abstracts, 104, 2017 | 3 | 2017 |
| On invariance and linear convergence of evolution strategies with augmented Lagrangian constraint handling A Atamna, A Auger, N Hansen Theoretical Computer Science 832, 68-97, 2020 | 2 | 2020 |
| Analysis of Randomized Adaptive Algorithms for Black-Box Continuous Constrained Optimization A Atamna Université Paris-Saclay (ComUE), 2017 | 1 | 2017 |
| Convex optimization with an interpolation-based projection and its application to deep learning R Akrour, A Atamna, J Peters Machine Learning 110 (8), 2267-2289, 2021 | | 2021 |
| HRI-RNN: A User-Robot Dynamics-Oriented RNN for Engagement Decrease Detection A Atamna, C Clavel INTERSPEECH 2020, 2020 | | 2020 |
Anne AugerInria, CMAP Ecole Polytechnique, IP ParisVerified email at inria.fr
