Ritesh Agarwal
Ritesh Agarwal
Software Engineer, Google
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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, ...
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
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
“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
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
Keyword bid optimization under cost per click constraints
PSR Pavagada, H Prakash, R Agarwal, V Ramaiyer
US Patent App. 12/702,690, 2011
Reinforcement learning in combinatorial action spaces
TWE Ie, J Vihan, J Wang, R Agarwal, CE Boutilier
US Patent App. 16/975,060, 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, ...
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