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» Approximation Algorithms for Min-Max Generalization Problems
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ICPR
2006
IEEE
16 years 3 months ago
Control Double Inverted Pendulum by Reinforcement Learning with Double CMAC Network
To accelerate the learning of reinforcement learning, many types of function approximation are used to represent state value. However function approximation reduces the accuracy o...
Siwei Luo, Yu Zheng, Ziang Lv
CORR
2011
Springer
202views Education» more  CORR 2011»
14 years 9 months ago
Multi-skill Collaborative Teams based on Densest Subgraphs
We consider the problem of identifying a team of skilled individuals for collaboration, in the presence of a social network. Each node in the input social network may be an expert...
Amita Gajewar, Atish Das Sarma
TIT
2008
112views more  TIT 2008»
15 years 1 months ago
Rainbow Network Flow of Multiple Description Codes
This paper is an enquiry into the interaction between multiple description coding (MDC) and network routing. We are mainly concerned with rate-distortion optimized network flow of...
Xiaolin Wu, Bin Ma, Nima Sarshar
UAI
2001
15 years 3 months ago
Iterative Markov Chain Monte Carlo Computation of Reference Priors and Minimax Risk
We present an iterative Markov chain Monte Carlo algorithm for computing reference priors and minimax risk for general parametric families. Our approach uses MCMC techniques based...
John D. Lafferty, Larry A. Wasserman
PROCEDIA
2010
113views more  PROCEDIA 2010»
15 years 9 days ago
Exploring utilisation of GPU for database applications
This study is devoted to exploring possible applications of GPU technology for acceleration of the database access. We use the n-gram based approximate text search engine as a tes...
Slawomir Walkowiak, Konrad Wawruch, Marita Nowotka...