132 citations
- Massachusetts Institute of TechnologyUS4 papers
- University of LübeckDE4 papers
- University of WashingtonUS4 papers
- Assumption CollegeUS3 papers
- Lehigh UniversityUS3 papers
- University of California San DiegoUS3 papers
- University of IowaUS3 papers
- University of MichiganUS3 papers
- University of Southern MississippiUS3 papers
- Virginia TechUS3 papers
- California University of PennsylvaniaUS2 papers
- Carnegie Mellon UniversityUS2 papers
Showing 2019 · cs.LGShow all
2 papers · 2 filters
cs.LG2019★ 1 cited
Potential-Based Advice for Stochastic Policy Learning
Baicen Xiao, Bhaskar Ramasubramanian, Andrew Clark +3
This paper augments the reward received by a reinforcement learning agent with potential functions in order to help the agent learn (possibly stochastic) optimal policies. We show…
cs.LG2019★ 3 cited
Predicting Urban Dispersal Events: A Two-Stage Framework through Deep Survival Analysis on Mobility Data
Amin Vahedian, Xun Zhou, Ling Tong +2
Urban dispersal events are processes where an unusually large number of people leave the same area in a short period. Early prediction of dispersal events is important in mitigatin…