Staerman, Guillaume

13 publications

AISTATS 2025 Signature Isolation Forest Marta Campi, Guillaume Staerman, Gareth W. Peters, Tomoko Masui

AISTATS 2025 UNHaP: Unmixing Noise from Hawkes Processes Virginie Loison, Guillaume Staerman, Thomas Moreau

TMLR 2024 A Pseudo-Metric Between Probability Distributions Based on Depth-Trimmed Regions Guillaume Staerman, Pavlo Mozharovskyi, Pierre Colombo, Stephan Clémençon, Florence d'Alché-Buc

ICMLW 2024 Unmixing Noise from Hawkes Process to Model Learned Physiological Events Guillaume Staerman, Virginie Loison, Thomas Moreau

AAAI 2024 Unsupervised Layer-Wise Score Aggregation for Textual OOD Detection Maxime Darrin, Guillaume Staerman, Eduardo Dadalto Câmara Gomes, Jackie C. K. Cheung, Pablo Piantanida, Pierre Colombo

TMLR 2023 A Halfspace-Mass Depth-Based Method for Adversarial Attack Detection Marine Picot, Federica Granese, Guillaume Staerman, Marco Romanelli, Francisco Messina, Pablo Piantanida, Pierre Colombo

ICML 2023 FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels Guillaume Staerman, Cédric Allain, Alexandre Gramfort, Thomas Moreau

ICML 2023 Hypothesis Transfer Learning with Surrogate Classification Losses: Generalization Bounds Through Algorithmic Stability Anass Aghbalou, Guillaume Staerman

NeurIPS 2022 Beyond Mahalanobis Distance for Textual OOD Detection Pierre Colombo, Eduardo Dadalto, Guillaume Staerman, Nathan Noiry, Pablo Piantanida

AISTATS 2021 When OT Meets MoM: Robust Estimation of Wasserstein Distance Guillaume Staerman, Pierre Laforgue, Pavlo Mozharovskyi, Florence d’Alché-Buc

ICML 2021 Generalization Bounds in the Presence of Outliers: A Median-of-Means Study Pierre Laforgue, Guillaume Staerman, Stephan Clémençon

AISTATS 2020 The Area of the Convex Hull of Sampled Curves: A Robust Functional Statistical Depth Measure Guillaume Staerman, Pavlo Mozharovskyi, Stéphan Clémen\con

ACML 2019 Functional Isolation Forest Guillaume Staerman, Pavlo Mozharovskyi, Stephan Clémençon, Florence d’Alché-Buc