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NN
2010
Springer
187views Neural Networks» more  NN 2010»
14 years 6 months ago
Efficient exploration through active learning for value function approximation in reinforcement learning
Appropriately designing sampling policies is highly important for obtaining better control policies in reinforcement learning. In this paper, we first show that the least-squares ...
Takayuki Akiyama, Hirotaka Hachiya, Masashi Sugiya...
AAAI
2011
13 years 12 months ago
Linear Dynamic Programs for Resource Management
Sustainable resource management in many domains presents large continuous stochastic optimization problems, which can often be modeled as Markov decision processes (MDPs). To solv...
Marek Petrik, Shlomo Zilberstein
HPCA
2009
IEEE
16 years 12 days ago
A first-order fine-grained multithreaded throughput model
Analytical modeling is an alternative to detailed performance simulation with the potential to shorten the development cycle and provide additional insights. This paper proposes a...
Xi E. Chen, Tor M. Aamodt
VLDB
2007
ACM
122views Database» more  VLDB 2007»
16 years 2 days ago
MIST: Distributed Indexing and Querying in Sensor Networks using Statistical Models
The modeling of high level semantic events from low level sensor signals is important in order to understand distributed phenomena. For such content-modeling purposes, transformat...
Arnab Bhattacharya, Anand Meka, Ambuj K. Singh
CIKM
2009
Springer
15 years 6 months ago
A social recommendation framework based on multi-scale continuous conditional random fields
This paper addresses the issue of social recommendation based on collaborative filtering (CF) algorithms. Social recommendation emphasizes utilizing various attributes informatio...
Xin Xin, Irwin King, Hongbo Deng, Michael R. Lyu