Équipes actuelles : | ALMASTY ALSOC APR BD CIAN ComplexNetworks DECISION DELYS LFI MOCAH MoVe NPA PEQUAN PolSys QI RO SMA SYEL |
Ancienne équipe : | ACASA |
Publications RO | 2023 | 2024 | Total |
---|---|---|---|
Livres | 0 | 0 | 0 |
Éditions de livres | 0 | 0 | 0 |
Articles de revues | 14 | 2 | 16 |
Chapitres de livres | 0 | 0 | 0 |
Conférences | 27 | 0 | 27 |
Habilitations | 0 | 0 | 0 |
Thèses | 2 | 0 | 2 |
- S. Angelopoulos : “Competitive Search in the Line and the Star with Predictions”, 48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023), vol. 272, Leibniz International Proceedings in Informatics (LIPIcs), Bordeaux, France, pp. 12:1-12:15, (Schloss Dagstuhl - Leibniz-Zentrum für Informatik) [Angelopoulos 2023a]
- S. Angelopoulos, Sh. Kamali : “Rényi-Ulam Games and Online Computation with Imperfect Advice”, 48th International Symposium on Mathematical Foundations of Computer Science (MFCS 2023), vol. 272, Leibniz International Proceedings in Informatics (LIPIcs), Bordeaux, France, pp. 13:1-13:15, (Schloss Dagstuhl - Leibniz-Zentrum für Informatik) [Angelopoulos 2023g]
- E. Bampis, B. Escoffier, N. Hahn, M. Xefteris : “Online TSP with Known Locations”, Algorithms and Data Structures Symposium (WADS), vol. 14079, Lecture Notes in Computer Science, Montreal, Canada, pp. 65-78, (Springer Nature Switzerland) [Bampis 2023a]
- E. Bampis, B. Escoffier, Th. Gouleakis, N. Hahn, K. Lakis, G. Shahkarami, M. Xefteris : “Learning-Augmented Online TSP on Rings, Trees, Flowers and (Almost) Everywhere Else”, 31st Annual European Symposium on Algorithms (ESA 2023), vol. 274, Leibniz International Proceedings in Informatics (LIPIcs), Amsterdam, Netherlands, pp. 12:1-12:17, (Schloss Dagstuhl - Leibniz-Zentrum für Informatik) [Bampis 2023b]
- P. Bendotti, L. Brunod‑Indrigo, Ph. Chrétienne, B. Escoffier : “Algorithms and complexity results for resource leveling problems”, ROADEF, Rennes, France [Bendotti 2023]
- C. Benjamins, E. Raponi, A. Janković, C. Doerr, M. Lindauer : “Self-Adjusting Weighted Expected Improvement for Bayesian Optimization”, Proceedings of Machine Learning Research (PMLR), Potsdam, Germany [Benjamins 2023a]
- P. Braun, N. Hahn, M. Hoefer, C. Schecker : “Delegated Online Search”, Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}, Macau, China, pp. 2528-2536, (International Joint Conferences on Artificial Intelligence Organization) [Braun 2023]
- G. Cenikj, G. Petelin, C. Doerr, P. Korosec, T. Eftimov : “DynamoRep: Trajectory-Based Population Dynamics for Classification of Black-box Optimization Problems”, GECCO '23: Proceedings of the Genetic and Evolutionary Computation Conference, Lisbon, Portugal, pp. 813-821, (ACM), (ISBN: 9798400701191) [Cenikj 2023]
- D. Chen, M. Buzdalov, C. Doerr, N. Dang : “Using Automated Algorithm Configuration for Parameter Control”, FOGA '23: Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, Potsdam, Germany, pp. 38-49, (ACM), (ISBN: 979-8-4007-0202-0) [Chen 2023]
- F. Clément, D. Vermetten, J. De Nobel, A. Jesus, L. Paquete, C. Doerr : “Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms”, GECCO '23: Genetic and Evolutionary Computation Conference, Lisbon, Portugal, pp. 1330-1338, (ACM) [Clément 2023]
- C. Doerr, D. Janett, J. Lengler : “Tight Runtime Bounds for Static Unary Unbiased Evolutionary Algorithms on Linear Functions”, Proceedings of the Genetic and Evolutionary Computation Conference, Lisbon, Portugal, pp. 1565-1574, (ACM) [Doerr 2023a]
- C. Doerr, H. Wang, D. Vermetten, Th. Bäck, J. De Nobel, F. Ye : “Benchmarking and analyzing iterative optimization heuristics with IOHprofiler”, GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation, Lisbon, Portugal, pp. 938-945, (ACM) [Doerr 2023b]
- B. Escoffier, O. Spanjaard, M. Tydrichová : “Algorithmic Recognition of 2-Euclidean Preferences”, Proceedings of ECAI 2023, vol. 372, Frontiers in Artificial Intelligence and Applications, Krakow (Cracovie), Poland, pp. 637-644, (IOS Press), (ISBN: 978-1-64368-437-6) [Escoffier 2023]
- N. Hahn, M. Xefteris : “The Covering Canadian Traveller Problem Revisited”, International Symposium on Mathematical Foundations of Computer Science, vol. 272, Leibniz International Proceedings in Informatics (LIPIcs), Bordeaux, France, (Schloss Dagstuhl - Leibniz-Zentrum für Informatik) [Hahn 2023]
- A. Kostovska, C. Doerr, S. Dzeroski, D. Kocev, P. Panov, T. Eftimov : “Explainable Model-specific Algorithm Selection for Multi-Label Classification”, Proc. of 2022 IEEE Symposium Series on Computational Intelligence (SSCI), Singapore, Singapore, pp. 39-46, (IEEE), (ISBN: 978-1-6654-8768-9) [Kostovska 2023b]
- A. Kostovska, D. Vermetten, S. Dzeroski, P. Panov, T. Eftimov, C. Doerr : “Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms”, Applications of Evolutionary Computation (EvoApplications 2023), vol. 13989, Lecture Notes in Computer Science, Brno, Czechia, pp. 253-268, (Springer), (ISBN: 978-3-031-30229-9) [Kostovska 2023d]
- A. Kostovska, G. Cenikj, D. Vermetten, A. Janković, A. Nikolikj, U. Skvorc, P. Korosec, C. Doerr, T. Eftimov : “PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization”, Proceedings of Machine Learning Research (PMLR), Potsdam, Germany [Kostovska 2023e]
- A. Nikolikj, C. Doerr, T. Eftimov : “RF+clust for Leave-One-Problem-Out Performance Prediction”, Applications of Evolutionary Computation, vol. 13989, Lecture Notes in Computer Science, Brno, Czechia, pp. 285-301, (Springer), (ISBN: 978-3-031-30229-9) [Nikolikj 2023a]
- A. Nikolikj, M. Pluháček, C. Doerr, P. Korosec, T. Eftimov : “Sensitivity Analysis of RF+clust for Leave-One-Problem-Out Performance Prediction”, 2023 IEEE Congress on Evolutionary Computation (CEC), Chicago, IL, United States, pp. 1-8, (IEEE), (ISBN: 979-8-3503-1458-8) [Nikolikj 2023c]
- A. Nikolikj, S. Dzeroski, M. Muñoz, C. Doerr, P. Korosec, T. Eftimov : “Algorithm Instance Footprint: Separating Easily Solvable and Challenging Problem Instances”, GECCO '23: Proceedings of the Genetic and Evolutionary Computation Conference, Lisbon, Portugal, pp. 529-537, (ACM), (ISBN: 9798400701191) [Nikolikj 2023d]
- A. Robbes, Kh. Salem : “A matheuristic for the 2D bounded-size cutting stock problem”, 24ème Congrès Annuel de la Société Française de Recherche Opérationnelle et Aide à la Décision, Rennes, France [Robbes 2023]
- Kh. Salem, A. Kramer, A. Robbes : “An arc-flow model for the job sequencing and tool switching problem with non-identical parallel machines”, 24ème Congrès Annuel de la Société Française de Recherche Opérationnelle et Aide à la Décision, Rennes, France [Salem 2023]
- M. Santoni, E. Raponi, R. De Leone, C. Doerr : “Comparison of Bayesian Optimization Algorithms for BBOB Problems in Dimensions 10 and 60”, GECCO '23 Companion: Proceedings of the Companion Conference on Genetic and Evolutionary Computation, Lisbon, Portugal, pp. 2390-2393, (ACM), (ISBN: 979-8-4007-0120-7) [Santoni 2023]
- I. Tarhan, J. Carlier, C. Hanen, A. Jouglet, A. Munier‑Kordon : “Parametrized analysis of an enumerative algorithm for a parallel machine scheduling problem”, 29th International European Conference on Parallel and Distributed Computing (EURO-PAR 2023), Limassol (Chypre), Cyprus [Tarhan 2023]
- H. Vaillaud, C. Hanen, E. Hyon, C. Enderli : “Target search with a radar on an airborne platform”, 2023 26th International Conference on Information Fusion (FUSION), Charleston, SC, United States, pp. 1-8, (IEEE), (ISBN: 979-8-89034-485-4) [Vaillaud 2023]
- D. Vermetten, F. Ye, C. Doerr : “Using Affine Combinations of BBOB Problems for Performance Assessment”, Proceedings of the Genetic and Evolutionary Computation Conference, Lisbon, Portugal, pp. 873-881, (ACM), (ISBN: 9798400701191) [Vermetten 2023a]
- D. Vermetten, F. Ye, Th. Bäck, C. Doerr : “MA-BBOB: Many-Affine Combinations of BBOB Functions for Evaluating AutoML Approaches in Noiseless Numerical Black-Box Optimization Contexts”, Proceedings of Machine Learning Research (PMLR), Potsdam, Germany [Vermetten 2023b]