• 
  Maria Luiza Costa Vianna. A Geometrical Approach to Estimate the Coverage Measure of the Area Explored by a Robot. Robotics [cs.RO]. Institut Polytechnique de Paris, 2023. English. ⟨NNT : 2023IPPAX115⟩. ⟨tel-04551631⟩
• 
  Thomas Wimmer, Peter Wonka, Maks Ovsjanikov. Back to 3D: Few-Shot 3D Keypoint Detection with Back-Projected 2D Features. 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Jun 2024, Seattle, WA, United States. ⟨hal-04550189⟩
• 
  Eric Goubault, Sylvie Putot. A Zonotopic Dempster-Shafer Approach to the Quantitative Verification of Neural Networks. 2024. ⟨hal-04546350v2⟩
• 
  Marianela Morales Elena. Unusual proof systems for modal logics with applications to decision problems. Logic in Computer Science [cs.LO]. Institut Polytechnique de Paris, 2023. English. ⟨NNT : 2023IPPAX129⟩. ⟨tel-04546959⟩
• 
  Carlos Pinzón Henao. Exploring fairness and privacy in machine learning. Artificial Intelligence [cs.AI]. Institut Polytechnique de Paris, 2023. English. ⟨NNT : 2023IPPAX126⟩. ⟨tel-04546889⟩
• 
  Georg Daniel Förster, Jérôme Idier, Leo Liberti, Antonio Mucherino, Jung-Hsin Lin, et al.. Characterization of the conformational space of intrinsically disordered proteins. XIIth International Conference NMR: a tool for biology, May 2022, Paris, France. ⟨hal-04545776⟩
• 
  Sayan Biswas. Comprendre et optimiser le compromis entre vie privée et utilité d'un point de vue fondamental. Artificial Intelligence [cs.AI]. Institut Polytechnique de Paris, 2023. English. ⟨NNT : 2023IPPAX092⟩. ⟨tel-04407120⟩
• 
  Taher Yacoub. Développement et implémentation d'une approche par fragments pour le design d'ARNs modifiés simple brin avec évaluation sur des protéines de liaison à l'ARN et un modèle d'étude la Bêta-Sécrétase 1. Complexité [cs.CC]. Université Paris-Saclay, 2024. Français. ⟨NNT : 2024UPASL002⟩. ⟨tel-04538513⟩
• 
  Benjamin Doerr, Timo Kötzing. Lower bounds from fitness levels made easy. GECCO '21: Genetic and Evolutionary Computation Conference, 2021, Lille, France. pp.1142-1150, ⟨10.1145/3449639.3459352⟩. ⟨hal-04486470⟩
• 
  Benjamin Doerr, Andrei Lissovoi, Pietro Oliveto. Evolving boolean functions with conjunctions and disjunctions via genetic programming. GECCO '19: Genetic and Evolutionary Computation Conference, 2019, Prague, Czech Republic. pp.1003-1011, ⟨10.1145/3321707.3321851⟩. ⟨hal-04484779⟩
• 
  Benjamin Doerr. An exponential lower bound for the runtime of the compact genetic algorithm on jump functions. FOGA '19: Foundations of Genetic Algorithms XV, 2019, Potsdam Germany, France. pp.25-33, ⟨10.1145/3299904.3340304⟩. ⟨hal-04484767⟩
• 
  Benjamin Doerr, Martin Krejca. Significance-based estimation-of-distribution algorithms. IEEE Transactions on Evolutionary Computation, 2020, 24 (6), pp.1483-1490. ⟨10.1109/TEVC.2019.2956633⟩. ⟨hal-04484793⟩
• 
  Benjamin Doerr, Martin Krejca. A simplified run time analysis of the univariate marginal distribution algorithm on LeadingOnes. Theoretical Computer Science, 2021, 851, pp.121-128. ⟨10.1016/J.TCS.2020.11.028⟩. ⟨hal-04485607⟩
• 
  Benjamin Doerr, Weijie Zheng. Working principles of binary differential evolution. Theoretical Computer Science, 2020, 801, pp.1103-1110. ⟨10.1145/3205455.3205623⟩. ⟨hal-04484791⟩
• 
  Benjamin Doerr, Sebastian Mayer. The recovery of ridge functions on the hypercube suffers from the curse of dimensionality. Journal of Complexity, 2021, 63, pp.101521. ⟨10.1016/j.jco.2020.101521⟩. ⟨hal-04485601⟩
• 
  Benjamin Doerr, Marvin Kunnemann. Improved Protocols and Hardness Results for the Two-Player Cryptogenography Problem. IEEE Transactions on Information Theory, 2020, 66 (9), pp.5729-5741. ⟨10.1109/TIT.2020.2978385⟩. ⟨hal-04484795⟩
• 
  Benjamin Doerr, Weijie Zheng. Sharp Bounds for Genetic Drift in Estimation of Distribution Algorithms. IEEE Transactions on Evolutionary Computation, 2020, 24 (6), pp.1140-1149. ⟨10.1109/TEVC.2020.2987361⟩. ⟨hal-04487372⟩
• 
  Benjamin Doerr, Carsten Witt, Jing Yang. Runtime analysis for self-adaptive mutation rates. Algorithmica, 2020, 83 (4), pp.1475-1482. ⟨10.1145/3205455.3205569⟩. ⟨hal-04485595⟩
• 
  Benjamin Doerr. Analyzing randomized search heuristics via stochastic domination. Evolutionary Computation in Combinatorial Optimization - 18th European Conference, EvoCOP 2018, 2018, Parma (Italie), Italy. pp.115-137, ⟨10.1016/j.tcs.2018.09.024⟩. ⟨hal-04484605⟩
• 
  Benjamin Doerr. An elementary analysis of the probability that a binomial random variable exceeds its expectation. Statistics and Probability Letters, 2018, 139, pp.67 - 74. ⟨10.1016/j.spl.2018.03.016⟩. ⟨hal-04484651⟩

2 788

1 088