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DATE
2008
IEEE
136views Hardware» more  DATE 2008»
14 years 3 months ago
A Framework of Stochastic Power Management Using Hidden Markov Model
- The effectiveness of stochastic power management relies on the accurate system and workload model and effective policy optimization. Workload modeling is a machine learning proce...
Ying Tan, Qinru Qiu
BMCBI
2010
104views more  BMCBI 2010»
13 years 8 months ago
Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies
Background: All polypeptide backbones have the potential to form amyloid fibrils, which are associated with a number of degenerative disorders. However, the likelihood that amyloi...
Maria Pamela C. David, Gisela P. Concepcion, Eduar...
EOR
2007
117views more  EOR 2007»
13 years 8 months ago
Simultaneous perturbation stochastic approximation of nonsmooth functions
A simultaneous perturbation stochastic approximation (SPSA) method has been developed in this paper, using the operators of perturbation with the Lipschitz density function. This ...
Vaida Bartkute, Leonidas Sakalauskas
ICIP
2004
IEEE
14 years 10 months ago
Estimation of mixtures of probabilistic pca with stochastic em for the 3d biplanar reconstruction of scoliotic rib cage
In this paper, we present a robust method for estimating the model parameters in a mixture of probabilistic principal component analyzers. This method is based on the Stochastic v...
François Destrempes, Jacques A. de Guise, M...
ECCV
2008
Springer
14 years 10 months ago
Learning for Optical Flow Using Stochastic Optimization
Abstract. We present a technique for learning the parameters of a continuousstate Markov random field (MRF) model of optical flow, by minimizing the training loss for a set of grou...
Yunpeng Li, Daniel P. Huttenlocher