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ORCIDAditya Mohan
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2020 – today
- 2024
[j4]Aditya Mohan
, Amy Zhang, Marius Lindauer:
Structure in Deep Reinforcement Learning: A Survey and Open Problems. J. Artif. Intell. Res. 79: 1167-1236 (2024)- [j3]Alexander Tornede, Difan Deng, Theresa Eimer, Joseph Giovanelli, Aditya Mohan, Tim Ruhkopf, Sarah Segel, Daphne Theodorakopoulos, Tanja Tornede, Henning Wachsmuth, Marius Lindauer:
AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks. Trans. Mach. Learn. Res. 2024 (2024) - [c7]Carolin Benjamins, Gjorgjina Cenikj, Ana Nikolikj, Aditya Mohan, Tome Eftimov, Marius Lindauer:
Instance Selection for Dynamic Algorithm Configuration with Reinforcement Learning: Improving Generalization. GECCO Companion 2024: 563-566 - [i8]Carolin Benjamins, Gjorgjina Cenikj, Ana Nikolikj, Aditya Mohan, Tome Eftimov, Marius Lindauer:
Instance Selection for Dynamic Algorithm Configuration with Reinforcement Learning: Improving Generalization. CoRR abs/2407.13513 (2024) - [i7]Jannis Becktepe, Julian Dierkes, Carolin Benjamins, Aditya Mohan, David Salinas, Raghu Rajan, Frank Hutter, Holger H. Hoos, Marius Lindauer, Theresa Eimer:
ARLBench: Flexible and Efficient Benchmarking for Hyperparameter Optimization in Reinforcement Learning. CoRR abs/2409.18827 (2024) - 2023
- [j2]Carolin Benjamins, Theresa Eimer, Frederik Schubert, Aditya Mohan, Sebastian Döhler, André Biedenkapp, Bodo Rosenhahn, Frank Hutter, Marius Lindauer:
Contextualize Me - The Case for Context in Reinforcement Learning. Trans. Mach. Learn. Res. 2023 (2023) - [j1]Tim Ruhkopf, Aditya Mohan, Difan Deng, Alexander Tornede, Frank Hutter, Marius Lindauer:
MASIF: Meta-learned Algorithm Selection using Implicit Fidelity Information. Trans. Mach. Learn. Res. 2023 (2023) - [c6]Aditya Mohan, Carolin Benjamins, Konrad Wienecke, Alexander Dockhorn, Marius Lindauer:
AutoRL Hyperparameter Landscapes. AutoML 2023: 13/1-27 - [c5]Mohammad Loni, Aditya Mohan, Mehdi Asadi, Marius Lindauer:
Learning Activation Functions for Sparse Neural Networks. AutoML 2023: 16/1-19 - [i6]Aditya Mohan, Carolin Benjamins, Konrad Wienecke, Alexander Dockhorn, Marius Lindauer:
AutoRL Hyperparameter Landscapes. CoRR abs/2304.02396 (2023) - [i5]Mohammad Loni, Aditya Mohan, Mehdi Asadi, Marius Lindauer:
Learning Activation Functions for Sparse Neural Networks. CoRR abs/2305.10964 (2023) - [i4]Alexander Tornede, Difan Deng, Theresa Eimer, Joseph Giovanelli, Aditya Mohan, Tim Ruhkopf, Sarah Segel, Daphne Theodorakopoulos, Tanja Tornede, Henning Wachsmuth, Marius Lindauer:
AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks. CoRR abs/2306.08107 (2023) - [i3]Aditya Mohan, Amy Zhang, Marius Lindauer:
Structure in Reinforcement Learning: A Survey and Open Problems. CoRR abs/2306.16021 (2023) - 2022
- [c4]Aditya Mohan, Jing Zhang, Rémi Cozot, Céline Loscos:
Consistent Multi- and Single-View HDR-Image Reconstruction from Single Exposures. WICED@Eurographics/EuroVis 2022: 37-44 - [i2]Carolin Benjamins, Theresa Eimer, Frederik Schubert, Aditya Mohan, André Biedenkapp, Bodo Rosenhahn, Frank Hutter, Marius Lindauer:
Contextualize Me - The Case for Context in Reinforcement Learning. CoRR abs/2202.04500 (2022) - [i1]Aditya Mohan, Tim Ruhkopf, Marius Lindauer:
Towards Meta-learned Algorithm Selection using Implicit Fidelity Information. CoRR abs/2206.03130 (2022)
2010 – 2019
- 2018
- [c3]Aditya Mohan, Nafis Uddin Khan:
Dataset Expansion and Accelerated Computation for Image Classification: A Practical Approach. ICACDS (2) 2018: 43-54
2000 – 2009
- 2005
- [c2]Aditya Mohan, Wei Hong Hong, David Gay, Philip Buonadonna, A. Mainwaring:
End-to-end performance characterization of Sensornet multi-hop routing. ICPS 2005: 27-36 - 2003
- [c1]Aditya Mohan, Vana Kalogeraki:
Speculative routing and update propagation: a kundali centric approach. ICC 2003: 343-347
Coauthor Index
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