Back
  1. Home
  2. Profile of Emmanuel KIEFFER (Unilu)
Profil

KIEFFER Emmanuel

Main Referenced Co-authors
BOUVRY, Pascal  (28)
DANOY, Grégoire  (22)
Nagih, Anass (9)
VARRETTE, Sébastien  (6)
PINEL, Frederic  (5)
Main Referenced Keywords
HPC (3); Private Equity (3); Bi-level optimization (2); Hyper-heuristics (2); Algorithms (1);
Main Referenced Unit & Research Centers
ULHPC - University of Luxembourg: High Performance Computing (8)
LuXDEM - University of Luxembourg: Luxembourg XDEM Research Centre (1)
Main Referenced Disciplines
Computer science (33)

Publications (total 33)

The most downloaded
437 downloads
Pinel, F., Yin, J.-X., Hundt, C., Kieffer, E., Varrette, S., Bouvry, P., & See, S. (2020). Evolving a Deep Neural Network Training Time Estimator. Communications in Computer and Information Science. doi:10.1007/978-3-030-41913-4_2 https://hdl.handle.net/10993/42856

The most cited

25 citations (Scopus®)

Duflo, G., Kieffer, E., Brust, M. R., Danoy, G., & Bouvry, P. (2019). A GP Hyper-Heuristic Approach for Generating TSP Heuristics. In 33rd IEEE International Parallel & Distributed Processing Symposium (IPDPS 2019). https://hdl.handle.net/10993/39841

Kieffer, E., Meyer, T., Gloukoviezoff, G., Lucius, H., & Bouvry, P. (2023). Learning private equity recommitment strategies for institutional investors. Frontiers in Artificial Intelligence in Finance. doi:10.3389/frai.2023.1014317
Peer reviewed

Fischbach, T. M., Kieffer, E., & Bouvry, P. (2023). Challenges in Automatic Software Optimisation: the energy efficiency case [Paper presentation]. INTERNATIONAL CONFERENCE ON OPTIMIZATION AND LEARNING (OLA2023).

Varrette, S., Kieffer, E., & Pinel, F. (2022). Optimizing the Resource and Job Management System of an Academic HPC and Research Computing Facility. In 21st IEEE Intl. Symp. on Parallel and Distributed Computing (ISPDC'22). Basel, Switzerland: IEEE Computer Society.
Peer reviewed

Varrette, S., Cartiaux, H., Peter, S., Kieffer, E., Valette, T., & Olloh, A. (2022). Management of an Academic HPC Research Computing Facility: The ULHPC Experience 2.0. In 6th High Performance Computing and Cluster Technologies Conference (HPCCT 2022). Fuzhou, China: Association for Computing Machinery (ACM). doi:10.1145/3560442.3560445
Peer reviewed

Dilmaghani, S., Brust, M., Ribeiro, C. H., Kieffer, E., Danoy, G., & Bouvry, P. (January 2022). From communities to protein complexes: A local community detection algorithm on PPI networks. PLoS ONE, 17 (1), 1-17. doi:10.1371/journal.pone.0260484
Peer Reviewed verified by ORBi

Kieffer, E., Duflo, G., Danoy, G., Varrette, S., & Bouvry, P. (2022). A RNN-Based Hyper-Heuristic for Combinatorial Problems. In A RNN-Based Hyper-Heuristic for Combinatorial Problems. doi:10.1007/978-3-031-04148-8_2
Peer reviewed

Varrette, S., Kieffer, E., Pinel, F., Krishnasamy, E., Peter, S., Cartiaux, H., & Besseron, X. (2021). RESIF 3.0: Toward a Flexible & Automated Management of User Software Environment on HPC facility. In ACM Practice and Experience in Advanced Research Computing (PEARC'21) (PEARC'21). Virtual Event, Unknown/unspecified: Association for Computing Machinery (ACM). doi:10.1145/3437359.3465600
Peer reviewed

Kieffer, E., Pinel, F., Meyer, T., Gloukoviezoff, G., Lucius, H., & Bouvry, P. (2021). Proximal Policy Optimisation for a Private Equity Recommitment System. In Springer CCIS series.
Peer reviewed

Kieffer, E., Pinel, F., Meyer, T., Gloukoviezoff, G., Lucius, H., & Bouvry, P. (2021). Evolutionary Learning of Private Equity Recommitment Strategies. In 2021 IEEE Symposium Series on Computational Intelligence (SSCI). doi:10.1109/SSCI50451.2021.9660088
Peer reviewed

Mainassara Chekaraou, A. W., Besseron, X., Rousset, A., Kieffer, E., & Peters, B. (2020). Predicting near-optimal skin distance in Verlet buffer approach for Discrete Element Method. In 10th IEEE Workshop on Parallel / Distributed Combinatorics and Optimization. doi:10.1109/IPDPSW50202.2020.00093
Peer reviewed

Pinel, F., Yin, J.-X., Hundt, C., Kieffer, E., Varrette, S., Bouvry, P., & See, S. (2020). Evolving a Deep Neural Network Training Time Estimator. Communications in Computer and Information Science. doi:10.1007/978-3-030-41913-4_2
Peer reviewed

Kieffer, E., Danoy, G., Brust, M. R., Bouvry, P., & Nagih, A. (2020). Tackling Large-Scale and Combinatorial Bi-Level Problems With a Genetic Programming Hyper-Heuristic. IEEE Transactions on Evolutionary Computation, 24 (1), 44--56. doi:10.1109/TEVC.2019.2906581
Peer reviewed

Rosalie, M., Kieffer, E., Brust, M. R., Danoy, G., & Bouvry, P. (2020). Bayesian optimisation to select Rössler system parameters used in Chaotic Ant Colony Optimisation for Coverage. Journal of Computational Science, 41, 101047. doi:10.1016/j.jocs.2019.101047
Peer Reviewed verified by ORBi

Varrette, S., Pinel, F., Kieffer, E., Danoy, G., & Bouvry, P. (2019). Automatic Software Tuning of Parallel Programs for Energy-Aware Executions. In Proc. of 13th Intl. Conf. on Parallel Processing and Applied Mathematics (PPAM 2019). Bialystok, Poland: Springer Verlag.
Peer reviewed

Duflo, G., Kieffer, E., Brust, M. R., Danoy, G., & Bouvry, P. (2019). A GP Hyper-Heuristic Approach for Generating TSP Heuristics. In 33rd IEEE International Parallel & Distributed Processing Symposium (IPDPS 2019).
Peer reviewed

Kieffer, E., Danoy, G., Bouvry, P., & Nagih, A. (2019). Tackling Large-Scale and Combinatorial Bi-level Problems with a Genetic Programming Hyper-heuristic. IEEE Transactions on Evolutionary Computation. doi:10.1109/TEVC.2019.2906581
Peer Reviewed verified by ORBi

Duflo, G., Kieffer, E., Danoy, G., & Bouvry, P. (29 January 2019). GP hyper-heuristic for the travelling salesman problem [Paper presentation]. OLA'2019 Int. Conference on Optimization and Learning, Bangkok, Thailand.

Kieffer, E. (2019). Co-evolutionary Hybrid Bi-level Optimization [Doctoral thesis, Unilu - University of Luxembourg]. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/38566

Musial, J., Kieffer, E., Guzek, M., Danoy, G., Wagle, S. S., Bouvry, P., & Blazewicz, J. (2019). Cloud Brokering with Bundles: Multi-objective Optimization of Services Selection. Foundations of Computing and Decision Sciences. doi:10.2478/fcds-2019-0020
Peer Reviewed verified by ORBi

Kieffer, E., Danoy, G., Bouvry, P., & Nagih, A. (2018). A Competitive Approach for Bi-Level Co-Evolution. In 2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). doi:10.1109/IPDPSW.2018.00101
Peer reviewed

Kieffer, E., Rosalie, M., Danoy, G., & Bouvry, P. (26 February 2018). Bayesian optimization to enhance coverage performance of a swarm of UAV with chaotic dynamics [Paper presentation]. International Workshop on Optimization and Learning: Challenges and Applications (OLA 2018), Alicante, Spain.

Ostaszewski, M., Kieffer, E., Danoy, G., Schneider, R., & Bouvry, P. (2018). Clustering approaches for visual knowledge exploration in molecular interaction networks. BMC Bioinformatics, 19 (1), 308. doi:10.1186/s12859-018-2314-z
Peer Reviewed verified by ORBi

Olszewski, M. A., Meder, J. A. A., Kieffer, E., Bleuse, R., Rosalie, M., Danoy, G., & Bouvry, P. (2018). Visualizing the Template of a Chaotic Attractor. In 26th International Symposium on Graph Drawing and Network Visualization (GD 2018).
Peer reviewed

Kieffer, E., Danoy, G., Bouvry, P., & Nagih, A. (2017). A new modeling approach for the biobjective exact optimization of satellite payload configuration. International Transactions in Operational Research. doi:10.1111/itor.12386
Peer reviewed

Kieffer, E., Danoy, G., Bouvry, P., & Nagih, A. (2017). A new Co-evolutionary Algorithm Based on Constraint Decomposition. In IPDPS. IEEE Computer Society.
Peer reviewed

Kieffer, E., Danoy, G., Bouvry, P., & Nagih, A. (2017). Bayesian Optimization Approach of General Bi-level Problems. In Proceedings of the Genetic and Evolutionary Computation Conference Companion (pp. 1614-1621). New York, United States: ACM. doi:10.1145/3067695.3082537
Peer reviewed

Kieffer, E., Danoy, G., Bouvry, P., & Nagih, A. (2016). Co-evolutionary approach based on constraint decomposition. In Co-evolutionary approach based on constraint decomposition.
Peer reviewed

Kieffer, E., Danoy, G., & Bouvry, P. (April 2016). On Bi-level approach for Scheduling problems [Paper presentation]. New Challenges in Scheduling Theory.

Kieffer, E., Guzek, M., Danoy, G., Bouvry, P., & Nagih, A. (2016). A Novel Co-evolutionary Approach for Constrained Genetic Algorithms. In Proceedings of the 2016 on Genetic and Evolutionary Computation Conference Companion (pp. 47--48). New York, NY, USA, Unknown/unspecified: ACM. doi:10.1145/2908961.2908969
Peer reviewed

Kieffer, E., Danoy, G., Bouvry, P., & Nagih, A. (2016). Hybrid mobility model with pheromones for UAV detection task. In Hybrid mobility model with pheromones for UAV detection task. doi:10.1109/SSCI.2016.7850104
Peer reviewed

Kieffer, E., Stathakis, A., Danoy, G., Bouvry, P., & Morelli, G. (2014). Bi-objective Exact Optimization of Satellite Payload Power Configuration. In VIII ALIO/EURO Workshop on Applied Combinatorial Optimization.
Peer reviewed

Kieffer, E., Stathakis, A., Danoy, G., Bouvry, P., Talbi, E.-G., & Morelli, G. (2014). Multi-Objective Evolutionary Approach for the Satellite Payload Power Optimization Problem. In IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2014).
Peer reviewed

Kieffer, E., Stathakis, A., Danoy, G., Talbi, E.-G., & Bouvry, P. (2014). Bi-objective Optimization of Satellite Payload Power Configuration. In International Conference on Metaheuristics and Nature Inspired Computing (META 2014).
Peer reviewed

Contact ORBilu