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2020 – today
- 2025
[i6]Piersilvio De Bartolomeis, Javier Abad, Guanbo Wang, Konstantin Donhauser, Raymond M. Duch, Fanny Yang, Issa J. Dahabreh:
Efficient Randomized Experiments Using Foundation Models. CoRR abs/2502.04262 (2025)- [i5]Riccardo Cadei, Ilker Demirel, Piersilvio De Bartolomeis, Lukas Lindorfer, Sylvia Cremer, Cordelia Schmid, Francesco Locatello:
Causal Lifting of Neural Representations: Zero-Shot Generalization for Causal Inferences. CoRR abs/2502.06343 (2025) - 2024
- [c3]Piersilvio De Bartolomeis, Javier Abad Martinez, Konstantin Donhauser, Fanny Yang:
Hidden yet quantifiable: A lower bound for confounding strength using randomized trials. AISTATS 2024: 1045-1053 - [c2]Piersilvio De Bartolomeis, Javier Abad, Konstantin Donhauser, Fanny Yang:
Detecting critical treatment effect bias in small subgroups. UAI 2024: 943-965 - [i4]Piersilvio De Bartolomeis, Javier Abad, Konstantin Donhauser, Fanny Yang:
Detecting critical treatment effect bias in small subgroups. CoRR abs/2404.18905 (2024) - 2023
- [j1]Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli:
Convex Reinforcement Learning in Finite Trials. J. Mach. Learn. Res. 24: 250:1-250:42 (2023) - [i3]Piersilvio De Bartolomeis, Jacob Clarysse, Amartya Sanyal, Fanny Yang:
How robust accuracy suffers from certified training with convex relaxations. CoRR abs/2306.06995 (2023) - [i2]Piersilvio De Bartolomeis, Javier Abad Martinez, Konstantin Donhauser, Fanny Yang:
Hidden yet quantifiable: A lower bound for confounding strength using randomized trials. CoRR abs/2312.03871 (2023) - 2022
- [c1]Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli:
Challenging Common Assumptions in Convex Reinforcement Learning. NeurIPS 2022 - [i1]Mirco Mutti, Riccardo De Santi, Piersilvio De Bartolomeis, Marcello Restelli:
Challenging Common Assumptions in Convex Reinforcement Learning. CoRR abs/2202.01511 (2022)
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