345 citations
- Microsoft (United States)US17 papers
- Microsoft Research Montréal (Canada)10 papers
- Carnegie Mellon UniversityUS4 papers
- Georgia Institute of TechnologyUS4 papers
- University College LondonGB4 papers
- University of Illinois Urbana-ChampaignUS4 papers
- Bellevue Hospital CenterUS3 papers
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- Microsoft Research New York City (United States)2 papers
- Microsoft Research (United Kingdom)GB2 papers
- Orange (France)FR2 papers
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Showing 2017Show all
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cs.LG2017★ 345 cited
Deep Reinforcement Learning that Matters
Peter Henderson, Riashat Islam, Philip Bachman +3
In recent years, significant progress has been made in solving challenging problems across various domains using deep reinforcement learning (RL). Reproducing existing work and acc…
cs.LG2017★ 53 cited
Learning Algorithms for Active Learning
Philip Bachman, Alessandro Sordoni, Adam Trischler
We introduce a model that learns active learning algorithms via metalearning. For a distribution of related tasks, our model jointly learns: a data representation, an item selectio…