| SlateQ: A tractable decomposition for reinforcement learning with recommendation sets E Ie, V Jain, J Wang, S Narvekar, R Agarwal, R Wu, HT Cheng, T Chandra, ... | 121 | 2019 |
| Reinforcement learning for slate-based recommender systems: A tractable decomposition and practical methodology E Ie, V Jain, J Wang, S Narvekar, R Agarwal, R Wu, HT Cheng, ... arXiv preprint arXiv:1905.12767, 2019 | 64 | 2019 |
| Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval T Wu, EKI Chio, HT Cheng, Y Du, S Rendle, D Kuzmin, R Agarwal, ... Proceedings of the 29th ACM International Conference on Information …, 2020 | 25 | 2020 |
| “I Know What You Feel”: Analyzing the Role of Conjunctions in Automatic Sentiment Analysis R Agarwal, TV Prabhakar, S Chakrabarty International Conference on Natural Language Processing, 28-39, 2008 | 14 | 2008 |
| Modeling Information Need of Users in Search Sessions K Halder, HT Cheng, EKI Chio, G Roumpos, T Wu, R Agarwal arXiv preprint arXiv:2001.00861, 2020 | 4 | 2020 |
| Keyword bid optimization under cost per click constraints PSR Pavagada, H Prakash, R Agarwal, V Ramaiyer US Patent App. 12/702,690, 2011 | 2 | 2011 |
| Reinforcement learning in combinatorial action spaces TWE Ie, J Vihan, J Wang, R Agarwal, CE Boutilier US Patent App. 16/975,060, 2021 | 1 | 2021 |
| Zero-Shot Transfer Learning for Query-Item Cold Start in Search Retrieval and Recommendations A Kumar, C Du, D Kuzmin, EH Chi, E Chio, HT Cheng, JR Anderson, ... | | 2020 |
