RO - Conference papers

Current teams :	ALMASTY ALSOC APR BD CIAN ComplexNetworks DECISION DELYS LFI MOCAH MoVe NPA PEQUAN PolSys QI RO SMA SYEL
Former team :	ACASA

Publications RO	2023	2024	Total
Books	0	0	0
Edited books	0	0	0
Journal articles	15	9	24
Book chapters	0	0	0
Conference papers	34	8	42
Habilitations	0	0	0
Thesis	2	0	2

LIP6

Th. Anani, F. Delbot, J.‑F. Pradat‑Peyre : “Comparaison expérimentale de métaheuristiques pour la sélection de variables dans le cadre de l'apprentissage automatique appliqué au domaine médical”, 23ème congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la Décision, Villeurbanne - Lyon, France [Anani 2022a]
Th. Anani, F. Delbot, J.‑F. Pradat‑Peyre : “Experimental Comparison of Metaheuristics for Feature Selection in Machine Learning in the Medical Context”, Artificial Intelligence Applications and Innovations, vol. AICT-647 (Part II), IFIP Advances in Information and Communication Technology, Hersonissos, Greece, pp. 194-205, (Springer International Publishing), (ISBN: 978-3-031-08336-5) [Anani 2022b]
S. Angelopoulos, Sh. Kamali, D. Zhang : “Online Search with Best-Price and Query-Based Predictions”, Thirty-Sixth AAAI Conference on Artificial Intelligence, AAAI 2022, vol. 36 (9), Proceedings of the AAAI Conference on Artificial Intelligence, Virtual event, United States, pp. 9652-9660 [Angelopoulos 2022b]
S. Angelopoulos, Sh. Kamali, K. Shadkami : “Online Bin Packing with Predictions”, Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}, vol. 36 (9), Vienna, Austria, pp. 4574-4580, (International Joint Conferences on Artificial Intelligence Organization) [Angelopoulos 2022c]
K. Antonov, E. Raponi, H. Wang, C. Doerr : “High Dimensional Bayesian Optimization with Kernel Principal Component Analysis”, 17^th Proceedings of Parallel Problem Solving from Nature - (PPSN) 2022, Dortmund, Germany, pp. 118-131 [Antonov 2022]
E. Bampis, B. Escoffier, M. Xefteris : “Canadian Traveller Problem with Predictions”, 20^th International Workshop on Approximation and Online Algorithms, WAOA 2022, vol. 13538, Lecture Notes in Computer Science, Potsdam, Germany, pp. 116-133 [Bampis 2022b]
E. Bampis, K. Dogeas, A. Kononov, G. Lucarelli, F. Pascual : “Scheduling with Untrusted Predictions”, Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}, Vienna, Austria, pp. 4581-4587, (International Joint Conferences on Artificial Intelligence Organization) [Bampis 2022e]
P. Bendotti, P. Fouilhoux, C. Rottner, Th. Vignon : “Overlapping decomposition in column generation”, PGMODAYS 2022, Palaiseau, France [Bendotti 2022b]
C. Benjamins, A. Janković, E. Raponi, K. Van der Blom, M. Lindauer, C. Doerr : “Towards Automated Design of Bayesian Optimization via Exploratory Landscape Analysis”, 6^th Workshop on Meta-Learning at NeurIPS 2022, New Orleans, United States [Benjamins 2022a]
C. Benjamins, E. Raponi, A. Janković, K. Van der Blom, M. Santoni, M. Lindauer, C. Doerr : “PI is back! Switching Acquisition Functions in Bayesian Optimization”, 2022 NeurIPS Workshop on Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems, New Orleans, United States [Benjamins 2022b]
A. Biedenkapp, N. Dang, M. Krejca, F. Hutter, C. Doerr : “Theory-inspired Parameter Control Benchmarks for Dynamic Algorithm Configuration”, GECCO '22: Genetic and Evolutionary Computation Conference, Boston, United States, pp. 766-775 [Biedenkapp 2022]
V. Bouquet, F. Delbot, Ch. Picouleau : “Partition de graphe sous contrainte de ratio de degré”, 23ème congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la Décision, Villeurbanne - Lyon, France [Bouquet 2022]
N. Bulanova, A. Buzdalova, C. Doerr : “Fast Re-Optimization of LeadingOnes with Frequent Changes”, 2022 IEEE Congress on Evolutionary Computation (CEC), 2022 IEEE Congress on Evolutionary Computation (CEC), Padua, Italy, pp. 1-8, (IEEE) [Bulanova 2022]
G. Cenikj, R. Lang, A. Engelbrecht, C. Doerr, P. Korosec, T. Eftimov : “SELECTOR: Selecting a Representative Benchmark Suite for Reproducible Statistical Comparison”, GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference, Boston, United States [Cenikj 2022]
S. Cohen, Ph. Fischbeck, T. Friedrich, M. Krejca, Th. Sauerwald : “Accelerated Information Dissemination on Networks with Local and Global Edges”, 29^th International Colloquium on Structural Information and Communication Complexity (SIROCCO), Paderborn, Germany, pp. 79-97 [Cohen 2022]
V. Cohen‑Addad, A. Epasto, S. Lattanzi, V. Mirrokni, A. Munoz Medina, D. Saulpic, Ch. Schwiegelshohn, S. Vassilvitskii : “Scalable Differentially Private Clustering via Hierarchically Separated Trees”, KDD '22: Proceedings of the 28^th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington DC, United States, pp. 221-230, (ACM), (ISBN: 978-1-4503-9385-0) [Cohen-Addad 2022a]
V. Cohen‑Addad, A. Gupta, L. Hu, H. Oh, D. Saulpic : “An Improved Local Search Algorithm for k-Median”, ACM-SIAM Symposium on Discrete Algorithms (SODA22), Alexandria (virtual event), VA, United States, pp. 1556-1612, (Society for Industrial and Applied Mathematics), (ISBN: 978-1-61197-707-3) [Cohen-Addad 2022b]
V. Cohen‑Addad, F. Mallmann‑Trenn, D. Saulpic : “A Massively Parallel Modularity-Maximizing Algorithm with Provable Guarantees”, PODC'22: Proceedings of the 2022 ACM Symposium on Principles of Distributed Computing, Salerno, Italy, pp. 356-365, (ACM) [Cohen-Addad 2022c]
V. Cohen‑Addad, F. Mallmann‑Trenn, D. Saulpic : “Community Recovery in the Degree-Heterogeneous Stochastic Block Model”, Proceedings of Machine Learning Research, vol. 178, Londres, United Kingdom, pp. 1662-1692, (PMLR) [Cohen-Addad 2022d]
V. Cohen‑Addad, K. Larsen, D. Saulpic, Ch. Schwiegelshohn : “Towards Optimal Lower Bounds for k-median and k-means Coresets”, Proceedings of the 54^th Annual ACM SIGACT Symposium on Theory of Computing, STOC 2022, Rome, Italy, pp. 1038-1051, (Association for Computing Machinery), (ISBN: 9781450392648) [Cohen-Addad 2022e]
M. Durand, F. Pascual : “Collective Schedules: Axioms and Algorithms”, Symposium on Algorithmic Game Theory - SAGT 2022, vol. 13584, Lecture Notes in Computer Science, Colchester, United Kingdom, pp. 454-471, (Springer International Publishing) [Durand 2022a]
M. Durand, F. Pascual : “Ordonnancements collectifs : Étude axiomatique et algorithmique”, 23ème congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la Décision, Villeurbanne - Lyon, France [Durand 2022b]
M. Durand, F. Pascual, O. Spanjaard : “A Non-utilitarian Discrete Choice Model for Preference Aggregation”, Proceedings of the 15^th Scalable Uncertainty Management conference (SUM 2022), vol. 13562, Lecture Notes in Computer Science, Paris, France, pp. 157-171, (Springer International Publishing) [Durand 2022c]
T. Friedrich, A. Göbel, M. Katzmann, M. Krejca, M. Pappik : “Algorithms for hard-constraint point processes via discretization”, International Computing and Combinatorics Conference (COCOON), Shenzhen, China, pp. 242-254, (Springer) [Friedrich 2022a]
T. Friedrich, T. Kötzing, M. Krejca, A. Rajabi : “Escaping Local Optima With Local Search: A Theory-Driven Discussion”, Parallel Problem Solving from Nature (PPSN) XVII, Dortmund, Germany, pp. 442-455 [Friedrich 2022b]
C. Hanen, M. Mallem, A. Munier‑Kordon : “Parameterized Complexity of Single-machine Scheduling with Precedence, Release Dates and Deadlines”, Models and Algorithms for Planning and Scheduling, Biella, Italy [Hanen 2022a]
A. Janković, D. Vermetten, A. Kostovska, J. De Nobel, T. Eftimov, C. Doerr : “Trajectory-based Algorithm Selection with Warm-starting”, 2022 IEEE Congress on Evolutionary Computation (CEC), 2022 IEEE Congress on Evolutionary Computation (CEC), Padua, Italy, pp. 1-8, (IEEE) [Janković 2022]
A. Kostovska, A. Janković, D. Vermetten, J. De Nobel, H. Wang, T. Eftimov, C. Doerr : “Per-run Algorithm Selection with Warm-starting using Trajectory-based Features”, 17^th Proceedings of Parallel Problem Solving from Nature - (PPSN) 2022, Dortmund, Germany, pp. 46-60 [Kostovska 2022a]
A. Kostovska, D. Vermetten, S. Dzeroski, C. Doerr, P. Korosec, T. Eftimov : “The Importance of Landscape Features for Performance Prediction of Modular CMA-ES Variants”, GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference, Boston, United States [Kostovska 2022b]
M. Mallem : “Parameterized complexity of a single machine scheduling problem”, 23ème congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la Décision, Villeurbanne - Lyon, France [Mallem 2022a]
M. Mallem, C. Hanen, A. Munier Kordon : “Parameterized complexity of a parallel machine scheduling problem”, International Symposium on Parameterized and Exact Computation (IPEC), Postdam, Germany [Mallem 2022b]
A. Pass‑Lanneau, P. Bendotti, Ph. Chrétienne, P. Fouilhoux : “Anchored solutions in robust combinatorial optimization: PGMO Phd Award 2022”, PGMO Days 2022, Palaiseau, France [Pass-Lanneau 2022a]
A. Pass‑Lanneau, P. Bendotti, Ph. Chrétienne, P. Fouilhoux : “Ancrage et robustesse pour le RCPSP: outils exacts et heuristiques”, 23ème congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la Décision, Villeurbanne - Lyon, France [Pass-Lanneau 2022b]
Q. Renau, J. Dréo, A. Peres, Y. Semet, C. Doerr, B. Doerr : “Automated Algorithm Selection for Radar Network Configuration”, GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference, Boston, United States [Renau 2022]
Th. Tournaire, Y. Jin, A. Aghasaryan, H. Castel‑Taleb, E. Hyon : “Factored Reinforcement Learning for Auto-scaling in Tandem Queues”, NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium, Budapest, Hungary, pp. 1-7, (IEEE) [Tournaire 2022]
R. Trajanov, A. Nikolikj, G. Cenikj, F. Teytaud, M. Videau, O. Teytaud, T. Eftimov, M. López‑Ibañez, C. Doerr : “Improving Nevergrad's Algorithm Selection Wizard NGOpt through Automated Algorithm Configuration”, Proc. of Parallel Problem Solving from Nature - PPSN XVII, Dortmund, Germany, pp. 18-31 [Trajanov 2022]
H. Vaillaud, C. Enderli, C. Hanen, E. Hyon : “Planification de la recherche d'une cible par une plateforme aéroportée”, 23ème congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la Décision, Villeurbanne - Lyon, France [Vaillaud 2022]
D. Vermetten, H. Wang, M. López‑Ibañez, C. Doerr, Th. Bäck : “Analyzing the Impact of Undersampling on the Benchmarking and Configuration of Evolutionary Algorithms”, GECCO '22: Proceedings of the Genetic and Evolutionary Computation Conference, Boston, United States [Vermetten 2022]
F. Ye, D. Vermetten, C. Doerr, Th. Bäck : “Non-Elitist Selection Can Improve the Performance of Irace”, 17^th Proceedings of Parallel Problem Solving from Nature - (PPSN) 2022, Dortmund, Germany, pp. 32-45 [Ye 2022b]