Hootan Nakhost

Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes

Cheng-Yu Hsieh, Chunliang Li, Chih‐Kuan Yeh et al. · 2023 · 250 citations · Full text

Computing, Computer Science, Computational Linguistics +8

Monte-Carlo exploration for deterministic planning

Hootan Nakhost, Martin Müller · 2009 · 78 citations

Computing, Autonomous Systems, Markov Decision Processes +14

Interpretable Sequence Learning for COVID-19 Forecasting

Sercan Ö. Arık, Chunliang Li, Jinsung Yoon et al. · arXiv (Cornell University) · 2020 · 59 citations · Full text

Computing, Health Informatics, Infectious Disease Control +17

Resource-Constrained Planning: A Monte Carlo Random Walk Approach

Hootan Nakhost, Jöerg Hoffmann, Martin Mueller · Proceedings of the International Conference on Automated Planning and Scheduling · 2012 · 56 citations · Full text

Management, Decision Sciences, Markov Decision Processes +6

Learning and Evaluating a Differentially Private Pre-trained Language Model

Shlomo Hoory, Amir Feder, Avichai Tendler et al. · 2021 · 39 citations · Full text

Computing, Linguistics, Computational Linguistics +13