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We build a deep reinforcement learning (RL) agent that can predict the likelihood of an individual testing positive for malaria by asking questions about their household.
Mobile text surveys: A smarter way to measure conservation’s impacts on people?
Game, Eddie · 2013
Earlier work this paper cites.
Playing atari with deep reinforcement learning
Mnih, Volodymyr, Kavukcuoglu, Koray, Silver, David, Graves, Alex, Antonoglou, Ioannis, Wierstra, Daan, and Riedmiller, Martin · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Kingma, Diederik and Ba, Jimmy · 2014
Earlier work this paper cites.
Going deeper with convolutions
Szegedy, Christian, Liu, Wei, Jia, Yangqing, Sermanet, Pierre, Reed, Scott E., Anguelov, Dragomir, Erhan, Dumitru, Vanhoucke, Vincent, and Rabinovich, Andrew · 2014
Cited alongside, same era.
Kenya Malaria Indicator Survey 2015
NMCP and Kenya National Bureau of Statistics (KNBS) and, ICF International · 2015
Cited alongside, same era.
Reasonet: Learning to stop reading in machine comprehension
Shen, Yelong, Huang, Po-Sen, Gao, Jianfeng, and Chen, Weizhu · 2016
Cited alongside, same era.
Ask the right questions: Active question reformulation with reinforcement learning
Buck, Christian, Bulian, Jannis, Ciaramita, Massimiliano, Gesmundo, Andrea, Houlsby, Neil, Gajewski, Wojciech, and Wang, Wei · 2017
Closest in time.
Sample efficient feature selection for factored mdps
Guo, Zhaohan Daniel and Brunskill, Emma · 2017
Closest in time.
In kenya, the path to elimination of malaria is lined with good preventions
Torfin, Svenn · 2017
Closest in time.
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