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ORCIDFabian R. Pieroth
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2020 – today
- 2024
[c3]Fabian Raoul Pieroth, Katherine E. Fitch, Lenz Belzner:
Detecting Influence Structures in Multi-Agent Reinforcement Learning. ICML 2024- [i5]Fabian R. Pieroth, Tuomas Sandholm:
Verifying Approximate Equilibrium in Auctions. CoRR abs/2408.11445 (2024) - 2023
- [j1]Martin Bichler
, Nils Kohring, Matthias Oberlechner, Fabian R. Pieroth:
Learning equilibrium in bilateral bargaining games. Eur. J. Oper. Res. 311(2): 660-678 (2023) - [c2]Nils Kohring, Fabian Raoul Pieroth, Martin Bichler:
Enabling First-Order Gradient-Based Learning for Equilibrium Computation in Markets. ICML 2023: 17327-17342 - [i4]Nils Kohring, Fabian R. Pieroth, Martin Bichler:
Enabling First-Order Gradient-Based Learning for Equilibrium Computation in Markets. CoRR abs/2303.09500 (2023) - [i3]Martin Bichler, Stephan B. Lunowa, Matthias Oberlechner, Fabian R. Pieroth, Barbara I. Wohlmuth:
On the Convergence of Learning Algorithms in Bayesian Auction Games. CoRR abs/2311.15398 (2023) - [i2]Fabian R. Pieroth, Nils Kohring, Martin Bichler:
Equilibrium Computation in Multi-Stage Auctions and Contests. CoRR abs/2312.11751 (2023) - 2022
- [c1]Xiyue Sun, Fabian R. Pieroth, Kyrill Schmid, Martin Wirsing, Lenz Belzner:
On Learning Stable Cooperation in the Iterated Prisoner's Dilemma with Paid Incentives. ICDCS Workshops 2022: 113-118 - [i1]Fabian R. Pieroth, Martin Bichler:
α-Rank-Collections: Analyzing Expected Strategic Behavior with Uncertain Utilities. CoRR abs/2211.10317 (2022)
Coauthor Index
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