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» Detection of Stochastic Processes
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140
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JCSS
2008
159views more  JCSS 2008»
15 years 3 months ago
Analysing distributed Internet worm attacks using continuous state-space approximation of process algebra models
Internet worms are classically described using SIR models and simulations, to capture the massive dynamics of the system. Here we are able to generate a differential equation-base...
Jeremy T. Bradley, Stephen T. Gilmore, Jane Hillst...
153
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KDD
2010
ACM
326views Data Mining» more  KDD 2010»
15 years 1 months ago
Document clustering via dirichlet process mixture model with feature selection
One essential issue of document clustering is to estimate the appropriate number of clusters for a document collection to which documents should be partitioned. In this paper, we ...
Guan Yu, Ruizhang Huang, Zhaojun Wang
141
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ICASSP
2009
IEEE
15 years 10 months ago
A hybrid method for deconvolution of Bernoulli-Gaussian processes
We investigate a hybrid method which improves the quality of state inference and parameter estimation in blind deconvolution of a sparse source modeled by a Bernoulli-Gaussian pro...
Sinan Yildirim, Ali Taylan Cemgil, Aysin Ertü...
133
Voted
ASPDAC
2009
ACM
161views Hardware» more  ASPDAC 2009»
15 years 10 months ago
Risk aversion min-period retiming under process variations
— Recent advances in statistical timing analysis (SSTA) achieve great success in computing arrival times under variations by extending sum and maximum operations to random variab...
Jia Wang, Hai Zhou
141
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ICML
1994
IEEE
15 years 7 months ago
Learning Without State-Estimation in Partially Observable Markovian Decision Processes
Reinforcement learning (RL) algorithms provide a sound theoretical basis for building learning control architectures for embedded agents. Unfortunately all of the theory and much ...
Satinder P. Singh, Tommi Jaakkola, Michael I. Jord...