| Distilling step-by-step! outperforming larger language models with less training data and smaller model sizes CY Hsieh, CL Li, CK Yeh, H Nakhost, Y Fujii, A Ratner, R Krishna, CY Lee, ... arXiv preprint arXiv:2305.02301, 2023 | 167 | 2023 |
| Monte-Carlo Exploration for Deterministic Planning. H Nakhost, M Müller IJCAI 9, 1766-1771, 2009 | 132 | 2009 |
| Interpretable sequence learning for COVID-19 forecasting S Arik, CL Li, J Yoon, R Sinha, A Epshteyn, L Le, V Menon, S Singh, ... Advances in Neural Information Processing Systems 33, 18807-18818, 2020 | 94 | 2020 |
| Resource-Constrained Planning: A Monte Carlo Random Walk Approach H Nakhost, J Hoffmann, M Müller | 66* | |
| Action elimination and plan neighborhood graph search: Two algorithms for plan improvement H Nakhost, M Müller Proceedings of the International Conference on Automated Planning and …, 2010 | 64 | 2010 |
| Learning and evaluating a differentially private pre-trained language model S Hoory, A Feder, A Tendler, S Erell, A Peled-Cohen, I Laish, H Nakhost, ... Findings of the Association for Computational Linguistics: EMNLP 2021, 1178-1189, 2021 | 54 | 2021 |
| Arvandherd: Parallel planning with a portfolio R Valenzano, H Nakhost, M Müller, J Schaeffer, N Sturtevant ECAI 2012, 786-791, 2012 | 45 | 2012 |
| Planning via random walk-driven local search F Xie, H Nakhost, M Müller Proceedings of the International Conference on Automated Planning and …, 2012 | 31 | 2012 |
| Sql-palm: Improved large language modeladaptation for text-to-sql R Sun, SO Arik, H Nakhost, H Dai, R Sinha, P Yin, T Pfister arXiv preprint arXiv:2306.00739, 2023 | 24 | 2023 |
| Arvand: the art of random walks H Nakhost, M Müller, R Valenzano, F Xie The, 15-16, 2011 | 21 | 2011 |
| Controlling commercial cooling systems using reinforcement learning J Luo, C Paduraru, O Voicu, Y Chervonyi, S Munns, J Li, C Qian, P Dutta, ... arXiv preprint arXiv:2211.07357, 2022 | 17 | 2022 |
| Improving local search for resource-constrained planning H Nakhost, J Hoffmann, M Müller Proceedings of the International Symposium on Combinatorial Search 1 (1), 81-82, 2010 | 16 | 2010 |
| Towards a Second Generation Random Walk Planner: An Experimental Exploration. H Nakhost, M Müller IJCAI, 2336-2342, 2013 | 14 | 2013 |
| Formal verification of the IEEE 802.1 D spanning tree protocol using extended Rebeca H Hojjat, H Nakhost, M Sirjani Electronic Notes in Theoretical Computer Science 159, 139-154, 2006 | 10 | 2006 |
| A Theoretical Framework for Studying Random Walk Planning H Nakhost, M Müller | 9 | 2012 |
| Arvandherd 2014 R Valenzano, H Nakhost, M Müller, J Schaeffer, N Sturtevant The Eighth International Planning Competition. Description of Participant …, 2014 | 8 | 2014 |
| Universal self-adaptive prompting X Wan, R Sun, H Nakhost, H Dai, JM Eisenschlos, SO Arik, T Pfister arXiv preprint arXiv:2305.14926, 2023 | 5 | 2023 |
| Random walk planning: Theory, practice, and application H Nakhost University of Alberta (Canada), 2013 | 5 | 2013 |
| A local Monte Carlo tree search approach in deterministic planning F Xie, H Nakhost, M Müller Proceedings of the AAAI Conference on Artificial Intelligence 25 (1), 2011 | 5 | 2011 |
| Towards a theory of random walk planning: Regress factors, fair homogeneous graphs and extensions H Nakhost, M Müller AI Communications 27 (4), 329-344, 2014 | 2 | 2014 |
Martin MüllerProfessor, Computing Science, University of AlbertaDirección de correo verificada de ualberta.ca
