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AI
1998
Springer
14 years 9 months ago
Model-Based Average Reward Reinforcement Learning
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
Prasad Tadepalli, DoKyeong Ok
66
Voted
IPPS
2008
IEEE
15 years 4 months ago
Providing flow based performance guarantees for buffered crossbar switches
Buffered crossbar switches are a special type of combined input-output queued switches with each crosspoint of the crossbar having small on-chip buffers. The introduction of cross...
Deng Pan, Yuanyuan Yang
INFOCOM
2005
IEEE
15 years 3 months ago
Optimal utility based multi-user throughput allocation subject to throughput constraints
— We consider the problem of scheduling multiple users sharing a time-varying wireless channel. (As an example, this is a model of scheduling in 3G wireless technologies, such as...
Matthew Andrews, Lijun Qian, Alexander L. Stolyar
106
Voted
ECCV
2008
Springer
15 years 8 months ago
Window Annealing over Square Lattice Markov Random Field
Monte Carlo methods and their subsequent simulated annealing are able to minimize general energy functions. However, the slow convergence of simulated annealing compared with more ...
Ho Yub Jung, Kyoung Mu Lee, Sang Uk Lee
117
Voted
ATAL
2007
Springer
15 years 1 months ago
A unified framework for multi-agent agreement
Multi-Agent Agreement problems (MAP) - the ability of a population of agents to search out and converge on a common state - are central issues in many multi-agent settings, from d...
Kiran Lakkaraju, Les Gasser