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» A finiteness theorem for Markov bases of hierarchical models
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AAAI
2006
13 years 8 months ago
Hard Constrained Semi-Markov Decision Processes
In multiple criteria Markov Decision Processes (MDP) where multiple costs are incurred at every decision point, current methods solve them by minimising the expected primary cost ...
Wai-Leong Yeow, Chen-Khong Tham, Wai-Choong Wong
GLOBECOM
2009
IEEE
13 years 5 months ago
Performance Modeling for Heterogeneous Wireless Networks with Multiservice Overflow Traffic
Performance modeling is important for the purpose of developing efficient dimensioning tools for large complicated networks. But it is difficult to achieve in heterogeneous wireles...
Qian Huang, King-Tim Ko, Villy Bæk Iversen
TFS
2008
174views more  TFS 2008»
13 years 7 months ago
Type-2 Fuzzy Markov Random Fields and Their Application to Handwritten Chinese Character Recognition
In this paper, we integrate type-2 (T2) fuzzy sets with Markov random fields (MRFs) referred to as T2 FMRFs, which may handle both fuzziness and randomness in the structural patter...
Jia Zeng, Zhi-Qiang Liu
CSREASAM
2004
13 years 8 months ago
The Key Authority - Secure Key Management in Hierarchical Public Key Infrastructures
We model a private key's life cycle as a finite state machine. The states are the key's phases of life and the transition functions describe tasks to be done with the key...
Alexander Wiesmaier, Marcus Lippert, Vangelis Kara...
ICML
2007
IEEE
14 years 8 months ago
Multi-task reinforcement learning: a hierarchical Bayesian approach
We consider the problem of multi-task reinforcement learning, where the agent needs to solve a sequence of Markov Decision Processes (MDPs) chosen randomly from a fixed but unknow...
Aaron Wilson, Alan Fern, Soumya Ray, Prasad Tadepa...