Hootan Nakhost
Hootan Nakhost
Doctor, Google
No verified email
Cited by
Cited by
Monte-Carlo Exploration for Deterministic Planning.
H Nakhost, M Müller
IJCAI 9, 1766-1771, 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
Resource-Constrained Planning: A Monte Carlo Random Walk Approach
H Nakhost, J Hoffmann, M Müller
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
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
Arvandherd: Parallel planning with a portfolio
R Valenzano, H Nakhost, M Müller, J Schaeffer, N Sturtevant
ECAI 2012, 786-791, 2012
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
Planning via random walk-driven local search
F Xie, H Nakhost, M Müller
Proceedings of the International Conference on Automated Planning and …, 2012
Arvand: the art of random walks
H Nakhost, M Müller, R Valenzano, F Xie
The, 15-16, 2011
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
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
Towards a Second Generation Random Walk Planner: An Experimental Exploration.
H Nakhost, M Müller
IJCAI, 2336-2342, 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
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
A Theoretical Framework for Studying Random Walk Planning
H Nakhost, M Müller
Arvandherd 2014
R Valenzano, H Nakhost, M Müller, J Schaeffer, N Sturtevant
The Eighth International Planning Competition. Description of Participant …, 2014
Random Walk Planning: Theory, Practice, and Application
H Nakhost
University of Alberta (Canada), 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
Universal Self-adaptive Prompting
X Wan, R Sun, H Nakhost, H Dai, JM Eisenschlos, SO Arik, T Pfister
arXiv preprint arXiv:2305.14926, 2023
Towards a theory of random walk planning: Regress factors, fair homogeneous graphs and extensions
H Nakhost, M Mueller
AI Communications 27 (4), 329-344, 2014
The system can't perform the operation now. Try again later.
Articles 1–20