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Conference and Workshop Papers
- 2023
[c6]Marius-Constantin Dinu, Markus Holzleitner, Maximilian Beck, Hoan Duc Nguyen, Andrea Huber, Hamid Eghbal-zadeh, Bernhard Alois Moser, Sergei V. Pereverzyev, Sepp Hochreiter, Werner Zellinger:
Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation. ICLR 2023- 2022
- [c5]Christian Alexander Steinparz, Thomas Schmied, Fabian Paischer, Marius-Constantin Dinu, Vihang Prakash Patil, Angela Bitto-Nemling, Hamid Eghbal-zadeh, Sepp Hochreiter:
Reactive Exploration to Cope With Non-Stationarity in Lifelong Reinforcement Learning. CoLLAs 2022: 441-469 - [c4]Kajetan Schweighofer, Marius-Constantin Dinu, Andreas Radler, Markus Hofmarcher, Vihang Prakash Patil, Angela Bitto-Nemling, Hamid Eghbal-zadeh, Sepp Hochreiter:
A Dataset Perspective on Offline Reinforcement Learning. CoLLAs 2022: 470-517 - [c3]Vihang Patil, Markus Hofmarcher, Marius-Constantin Dinu, Matthias Dorfer, Patrick M. Blies, Johannes Brandstetter, José Antonio Arjona-Medina, Sepp Hochreiter:
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution. ICML 2022: 17531-17572 - 2021
- [c2]Werner Zellinger, Natalia Shepeleva, Marius-Constantin Dinu, Hamid Eghbal-zadeh, Hoan Duc Nguyen, Bernhard Nessler, Sergei V. Pereverzyev, Bernhard Alois Moser:
The balancing principle for parameter choice in distance-regularized domain adaptation. NeurIPS 2021: 20798-20811 - 2020
- [c1]Marius-Constantin Dinu, Markus Hofmarcher, Vihang Prakash Patil, Matthias Dorfer, Patrick M. Blies, Johannes Brandstetter, Jose A. Arjona-Medina, Sepp Hochreiter:
XAI and Strategy Extraction via Reward Redistribution. xxAI@ICML 2020: 177-205
Informal and Other Publications
- 2024
- [i6]Marius-Constantin Dinu, Claudiu Leoveanu-Condrei, Markus Holzleitner, Werner Zellinger, Sepp Hochreiter:
SymbolicAI: A framework for logic-based approaches combining generative models and solvers. CoRR abs/2402.00854 (2024) - [i5]Ajay Patel, Markus Hofmarcher, Claudiu Leoveanu-Condrei, Marius-Constantin Dinu, Chris Callison-Burch, Sepp Hochreiter:
Large Language Models Can Self-Improve At Web Agent Tasks. CoRR abs/2405.20309 (2024) - 2023
- [i4]Marius-Constantin Dinu, Markus Holzleitner, Maximilian Beck, Hoan Duc Nguyen, Andrea Huber, Hamid Eghbal-zadeh, Bernhard Alois Moser
, Sergei V. Pereverzyev, Sepp Hochreiter, Werner Zellinger:
Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation. CoRR abs/2305.01281 (2023) - 2022
- [i3]Christian Alexander Steinparz, Thomas Schmied, Fabian Paischer, Marius-Constantin Dinu, Vihang Patil, Angela Bitto-Nemling, Hamid Eghbal-zadeh, Sepp Hochreiter:
Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning. CoRR abs/2207.05742 (2022) - 2021
- [i2]Kajetan Schweighofer, Markus Hofmarcher, Marius-Constantin Dinu, Philipp Renz, Angela Bitto-Nemling, Vihang Patil, Sepp Hochreiter:
Understanding the Effects of Dataset Characteristics on Offline Reinforcement Learning. CoRR abs/2111.04714 (2021) - 2020
- [i1]Vihang Prakash Patil, Markus Hofmarcher, Marius-Constantin Dinu, Matthias Dorfer, Patrick M. Blies, Johannes Brandstetter, Jose A. Arjona-Medina, Sepp Hochreiter:
Align-RUDDER: Learning From Few Demonstrations by Reward Redistribution. CoRR abs/2009.14108 (2020)
Coauthor Index
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