Adaptive scientific simulations require that periodic repartitioning occur dynamically throughout the course of the computation. The repartitionings should be computed so as to mi...
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
Visualizing large-scale online social network is a challenging yet essential task. This paper presents HiMap, a system that visualizes it by clustered graph via hierarchical group...
Lei Shi, Nan Cao, Shixia Liu, Weihong Qian, Li Tan...
This paper presents an updated version of the adaptive learning particle swarm optimizer (ALPSO) [6], we call it ALPSO-II. In order to improve the performance of ALPSO on multi-mod...
This paper presents a novel method that effectively combines both control variates and importance sampling in a sequential Monte Carlo context. The radiance estimates computed dur...