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Markus Peschl
Markus Peschl
Qualcomm AI Research
Dirección de correo verificada de qti.qualcomm.com - Página principal
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Robust scheduling with GFlowNets
DW Zhang, C Rainone, M Peschl, R Bondesan
International Conference on Learning Representations (ICLR) 2023, 2023
262023
MORAL: Aligning AI with Human Norms through Multi-Objective Reinforced Active Learning
M Peschl, A Zgonnikov, FA Oliehoek, LC Siebert
AAMAS '22: Proceedings of the 21st International Conference on Autonomous …, 2022
172022
Training for implicit norms in deep reinforcement learning agents through adversarial multi-objective reward optimization
M Peschl
Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 275-276, 2021
52021
Learning perturbations for soft-output linear mimo demappers
DE Worrall, M Peschl, A Behboodi, R Bondesan
GLOBECOM 2022-2022 IEEE Global Communications Conference, 5213-5218, 2022
12022
Robust scheduling with generative flow networks
C Rainone, WD Zhang, R Bondesan, M Peschl, M Gagrani, W Jeon, ...
US Patent App. 18/459,277, 2024
2024
Lattice reduction-aided perturbed additive demapper for multiple-input multiple-output signal detection
M Peschl, DE Worrall, A Behboodi, R Bondesan, P Sadeghi, S Barghi
US Patent App. 18/155,454, 2023
2023
Aligning AI with Human Norms: Multi-Objective Deep Reinforcement Learning with Active Preference Elicitation
M Peschl
2021
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