| Hybrid reward architecture for reinforcement learning H Van Seijen, M Fatemi, J Romoff, R Laroche, T Barnes, J Tsang Advances in neural information processing systems 30, 2017 | 326 | 2017 |
| Safe policy improvement with baseline bootstrapping R Laroche, P Trichelair, RT Des Combes International conference on machine learning, 3652-3661, 2019 | 246 | 2019 |
| Learning dynamic belief graphs to generalize on text-based games A Adhikari, X Yuan, MA Côté, M Zelinka, MA Rondeau, R Laroche, ... Advances in Neural Information Processing Systems 33, 3045-3057, 2020 | 121 | 2020 |
| Contextual bandit for active learning: Active thompson sampling D Bouneffouf, R Laroche, T Urvoy, R Féraud, R Allesiardo Neural Information Processing: 21st International Conference, ICONIP 2014 …, 2014 | 103 | 2014 |
| When does return-conditioned supervised learning work for offline reinforcement learning? D Brandfonbrener, A Bietti, J Buckman, R Laroche, J Bruna Advances in Neural Information Processing Systems 35, 1542-1553, 2022 | 88 | 2022 |
| Counting to explore and generalize in text-based games X Yuan, MA Côté, A Sordoni, R Laroche, RT Combes, M Hausknecht, ... arXiv preprint arXiv:1806.11525, 2018 | 65 | 2018 |
| Transfer reinforcement learning with shared dynamics R Laroche, M Barlier Proceedings of the AAAI conference on artificial intelligence 31 (1), 2017 | 65 | 2017 |
| Hybrid reward architecture for reinforcement learning HH Van Seijen, SMF Booshehri, RMH Laroche, JS Romoff US Patent 10,977,551, 2021 | 59 | 2021 |
| Score-based inverse reinforcement learning L El Asri, B Piot, M Geist, R Laroche, O Pietquin International Conference on Autonomous Agents and Multiagent Systems (AAMAS …, 2016 | 53 | 2016 |
| Reinforcement learning algorithm selection R Laroche, R Feraud ICLR, 2018 | 42 | 2018 |
| Safe policy improvement with soft baseline bootstrapping K Nadjahi, R Laroche, R Tachet des Combes Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020 | 36 | 2020 |
| Transfer Learning for User Adaptation in Spoken Dialogue Systems. A Genevay, R Laroche AAMAS, 975-983, 2016 | 34 | 2016 |
| Human-machine dialogue as a stochastic game M Barlier, J Perolat, R Laroche, O Pietquin 16th Annual SIGdial Meeting on Discourse and Dialogue (SIGDIAL 2015), 2015 | 31 | 2015 |
| NASTIA: Negotiating Appointment Setting Interface. L El Asri, R Lemonnier, R Laroche, O Pietquin, H Khouzaimi LREC, 266-271, 2014 | 31 | 2014 |
| Multi-advisor reinforcement learning R Laroche, M Fatemi, J Romoff, H van Seijen arXiv preprint arXiv:1704.00756, 2017 | 30 | 2017 |
| Reward function learning for dialogue management L El Asri, R Laroche, O Pietquin STAIRS 2012, 95-106, 2012 | 30 | 2012 |
| Decentralized exploration in multi-armed bandits R Féraud, R Alami, R Laroche International Conference on Machine Learning, 1901-1909, 2019 | 29 | 2019 |
| Reward shaping for statistical optimisation of dialogue management L El Asri, R Laroche, O Pietquin Statistical Language and Speech Processing: First International Conference …, 2013 | 29 | 2013 |
| On value function representation of long horizon problems L Lehnert, R Laroche, H van Seijen Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 27 | 2018 |
| Discrete compositional representations as an abstraction for goal conditioned reinforcement learning R Islam, H Zang, A Goyal, AM Lamb, K Kawaguchi, X Li, R Laroche, ... Advances in Neural Information Processing Systems 35, 3885-3899, 2022 | 26* | 2022 |
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