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
192016
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
182015
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
152017
COmparing Continuous Optimizers: numbbo
N Hansen, D Brockhoff, O Mersmann, T Tusar, D Tusar, OA ElHara, ...
COCO on Github, 2019
92019
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
52019
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
A Principled Approach to Analyze Expressiveness and Accuracy of Graph Neural Networks
A Atamna, N Sokolovska, JC Crivello
International Symposium on Intelligent Data Analysis, 27-39, 2020
22020
SPI-GCN: A Simple Permutation-Invariant Graph Convolutional Network
A Atamna, N Sokolovska, JC Crivello
22019
On invariance and linear convergence of evolution strategies with augmented Lagrangian constraint handling
A Atamna, A Auger, N Hansen
Theoretical Computer Science, 2018
12018
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
arXiv preprint arXiv:2011.07016, 2020
2020
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