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ORCIDKonstantinos Varelas
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2020 – today
- 2021
[b1]Konstantinos Varelas:
Randomized Derivative Free Optimization via CMA-ES and Sparse Techniques - Applications to Radars. (Optimisation sans dérivées stochastique via CMA-ES et Techniques Sparses - Applications Radars). Polytechnic Institute of Paris, France, 2021- 2020
- [j1]Konstantinos Varelas, Ouassim Ait ElHara, Dimo Brockhoff, Nikolaus Hansen, Duc Manh Nguyen, Tea Tusar
, Anne Auger:
Benchmarking large-scale continuous optimizers: The bbob-largescale testbed, a COCO software guide and beyond. Appl. Soft Comput. 97(Part): 106737 (2020) - [c4]Konstantinos Varelas, Anne Auger, Nikolaus Hansen:
Sparse Inverse Covariance Learning for CMA-ES with Graphical Lasso. PPSN (1) 2020: 707-718 - [i2]Mathieu Klein, Thomas Carpentier, Eric Jeanclaude, Rami Kassab, Konstantinos Varelas, Nico de Bruijn, Frédéric Barbaresco, Yann Briheche, Yann Semet, Florence Aligne:
AI-Augmented Multi Function Radar Engineering with Digital Twin: Towards Proactivity. CoRR abs/2006.12384 (2020)
2010 – 2019
- 2019
- [c3]Konstantinos Varelas:
Benchmarking large scale variants of CMA-ES and L-BFGS-B on the bbob-largescale testbed. GECCO (Companion) 2019: 1937-1945 - [c2]Konstantinos Varelas, Marie-Ange Dahito:
Benchmarking multivariate solvers of SciPy on the noiseless testbed. GECCO (Companion) 2019: 1946-1954 - [i1]Ouassim Ait ElHara, Konstantinos Varelas, Duc Manh Nguyen, Tea Tusar, Dimo Brockhoff, Nikolaus Hansen, Anne Auger:
COCO: The Large Scale Black-Box Optimization Benchmarking (bbob-largescale) Test Suite. CoRR abs/1903.06396 (2019) - 2018
- [c1]Konstantinos Varelas, Anne Auger, Dimo Brockhoff, Nikolaus Hansen, Ouassim Ait ElHara, Yann Semet, Rami Kassab, Frédéric Barbaresco:
A Comparative Study of Large-Scale Variants of CMA-ES. PPSN (1) 2018: 3-15
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