Asma Atamna
Title
Cited by
Cited by
Year
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
252014
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
232016
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
212015
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
172017
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
10
COCO documentation repository
D Brockhoff, N Hansen, O Mersmann, R Ros, D Tusar, T Tusar
URL http://github. com/numbbo/coco-doc, 2017
82017
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
72016
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
62019
SPI-GCN: a simple permutation-invariant graph convolutional network
A Atamna, N Sokolovska, JC Crivello
42019
A Principled Approach to Analyze Expressiveness and Accuracy of Graph Neural Networks.
A Atamna, N Sokolovska, JC Crivello
IDA, 27-39, 2020
32020
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
32017
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
22020
Analysis of Randomized Adaptive Algorithms for Black-Box Continuous Constrained Optimization
A Atamna
Universitť Paris-Saclay (ComUE), 2017
12017
Learning Policies for Object Manipulation with Robot Swarms
GHW Gebhardt, K Daun, M Schnaubelt, G Neumann
Advanced Robotics, 0
1
Convex optimization with an interpolation-based projection and its application to deep learning
R Akrour, A Atamna, J Peters
Machine Learning, 1-23, 2021
2021
HRI-RNN: A User-Robot Dynamics-Oriented RNN for Engagement Decrease Detection
A Atamna, C Clavel
INTERSPEECH 2020, 2020
2020
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Articles 1–16