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2020 – today
- 2024
[j2]Elizabeth Baldwin
, Martin Bichler, Maximilian Fichtl, Paul Klemperer:
Strong substitutes: structural properties, and a new algorithm for competitive equilibrium prices. Math. Program. 203(1): 611-643 (2024)- 2023
- [c2]Martin Bichler, Maximilian Fichtl, Matthias Oberlechner:
Computing Bayes Nash Equilibrium Strategies in Auction Games via Simultaneous Online Dual Averaging. EC 2023: 294 - 2022
- [c1]Eleni Batziou, Martin Bichler, Maximilian Fichtl:
Core-Stability in Assignment Markets with Financially Constrained Buyers. EC 2022: 473-474 - [i5]Eleni Batziou, Martin Bichler, Maximilian Fichtl:
Core-Stability in Assignment Markets with Financially Constrained Buyers. CoRR abs/2205.06132 (2022) - [i4]Maximilian Fichtl, Matthias Oberlechner, Martin Bichler:
Computing Bayes Nash Equilibrium Strategies in Auction Games via Simultaneous Online Dual Averaging. CoRR abs/2208.02036 (2022) - [i3]Maximilian Fichtl:
Computing Candidate Prices in Budget-Constrained Product-Mix Auctions. CoRR abs/2208.02633 (2022) - 2021
- [j1]Martin Bichler, Maximilian Fichtl, Stefan Heidekrüger, Nils Kohring, Paul Sutterer:
Learning equilibria in symmetric auction games using artificial neural networks. Nat. Mach. Intell. 3(8): 687-695 (2021) - [i2]Stefan Heidekrüger, Paul Sutterer, Nils Kohring, Maximilian Fichtl, Martin Bichler:
Equilibrium Learning in Combinatorial Auctions: Computing Approximate Bayesian Nash Equilibria via Pseudogradient Dynamics. CoRR abs/2101.11946 (2021) - [i1]Maximilian Fichtl:
On the Expressiveness of Assignment Messages. CoRR abs/2107.05051 (2021)
Coauthor Index
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