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Matthias Gerstgrasser
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2020 – today
- 2024
- [c10]Omar Shaikh, Kristina Gligoric, Ashna Khetan, Matthias Gerstgrasser, Diyi Yang, Dan Jurafsky:
Grounding Gaps in Language Model Generations. NAACL-HLT 2024: 6279-6296 - [i9]Matthias Gerstgrasser, Rylan Schaeffer, Apratim Dey, Rafael Rafailov, Henry Sleight, John Hughes, Tomasz Korbak, Rajashree Agrawal, Dhruv Pai, Andrey Gromov, Daniel A. Roberts, Diyi Yang, David L. Donoho, Sanmi Koyejo:
Is Model Collapse Inevitable? Breaking the Curse of Recursion by Accumulating Real and Synthetic Data. CoRR abs/2404.01413 (2024) - [i8]Joshua Kazdan, Rylan Schaeffer, Apratim Dey, Matthias Gerstgrasser, Rafael Rafailov, David L. Donoho, Sanmi Koyejo:
Collapse or Thrive? Perils and Promises of Synthetic Data in a Self-Generating World. CoRR abs/2410.16713 (2024) - 2023
- [c9]Matthias Gerstgrasser, Tom Danino, Sarah Keren:
Selectively Sharing Experiences Improves Multi-Agent Reinforcement Learning. AAMAS 2023: 2433-2435 - [c8]Matthias Gerstgrasser, David C. Parkes:
Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning. ICML 2023: 11213-11236 - [c7]Matthias Gerstgrasser, Tom Danino, Sarah Keren:
Selectively Sharing Experiences Improves Multi-Agent Reinforcement Learning. NeurIPS 2023 - [i7]Matthias Gerstgrasser, Tom Danino, Sarah Keren:
Selectively Sharing Experiences Improves Multi-Agent Reinforcement Learning. CoRR abs/2311.00865 (2023) - [i6]Omar Shaikh, Kristina Gligoric, Ashna Khetan, Matthias Gerstgrasser, Diyi Yang, Dan Jurafsky:
Grounding or Guesswork? Large Language Models are Presumptive Grounders. CoRR abs/2311.09144 (2023) - 2022
- [c6]Matthias Gerstgrasser, Rakshit Trivedi, David C. Parkes:
CrowdPlay: Crowdsourcing Human Demonstrations for Offline Learning. ICLR 2022 - [i5]Gianluca Brero, Alon Eden, Darshan Chakrabarti, Matthias Gerstgrasser, Vincent Li, David C. Parkes:
Learning Stackelberg Equilibria and Applications to Economic Design Games. CoRR abs/2210.03852 (2022) - [i4]Matthias Gerstgrasser, David C. Parkes:
Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning. CoRR abs/2210.11942 (2022) - 2021
- [c5]Gianluca Brero, Alon Eden, Matthias Gerstgrasser, David C. Parkes, Duncan Rheingans-Yoo:
Reinforcement Learning of Sequential Price Mechanisms. AAAI 2021: 5219-5227 - [i3]Ofir Abu, Matthias Gerstgrasser, Jeffrey S. Rosenschein, Sarah Keren:
Promoting Resilience in Multi-Agent Reinforcement Learning via Confusion-Based Communication. CoRR abs/2111.06614 (2021) - 2020
- [i2]Gianluca Brero, Alon Eden, Matthias Gerstgrasser, David C. Parkes, Duncan Rheingans-Yoo:
Reinforcement Learning of Simple Indirect Mechanisms. CoRR abs/2010.01180 (2020)
2010 – 2019
- 2019
- [j2]Matthias Gerstgrasser:
Reverse auctions are different from auctions. Inf. Process. Lett. 147: 49-54 (2019) - [c4]Matthias Gerstgrasser, Paul W. Goldberg
, Bart de Keijzer, Philip Lazos, Alexander Skopalik:
Multi-Unit Bilateral Trade. AAAI 2019: 1973-1980 - 2018
- [b1]Matthias Gerstgrasser:
Market intermediation: information, computation, and incentives. University of Oxford, UK, 2018 - [c3]Matthias Gerstgrasser:
On the Complexity of Optimal Correlated Auctions and Reverse Auctions. AAMAS 2018: 605-613 - [i1]Matthias Gerstgrasser, Paul W. Goldberg, Bart de Keijzer, Philip Lazos, Alexander Skopalik:
Multi-unit Bilateral Trade. CoRR abs/1811.05130 (2018) - 2017
- [c2]Wolfgang Fruehwirt
Bayesian Gaussian Process Classification from Event-Related Brain Potentials in Alzheimer's Disease. AIME 2017: 65-75 - 2016
- [j1]Matthias Gerstgrasser, Sarah Nicholls, Michael Stout, Katherine Smart, Chris Powell
A Bayesian approach to analyzing phenotype microarray data enables estimation of microbial growth parameters. J. Bioinform. Comput. Biol. 14(3): 1650007:1-1650007:23 (2016) - [c1]Matthias Gerstgrasser, Paul W. Goldberg
Revenue Maximization for Market Intermediation with Correlated Priors. SAGT 2016: 273-285
Coauthor Index
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