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» Graph model selection using maximum likelihood
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IEEEHPCS
2010
13 years 6 months ago
Reducing memory requirements of stream programs by graph transformations
Stream languages explicitly describe fork-join parallelism and pipelines, offering a powerful programming model for many-core Multi-Processor Systems on Chip (MPSoC). In an embedd...
Pablo de Oliveira Castro, Stéphane Louise, ...
ICDM
2009
IEEE
152views Data Mining» more  ICDM 2009»
13 years 6 months ago
A Sparsification Approach for Temporal Graphical Model Decomposition
Temporal causal modeling can be used to recover the causal structure among a group of relevant time series variables. Several methods have been developed to explicitly construct te...
Ning Ruan, Ruoming Jin, Victor E. Lee, Kun Huang
LREC
2010
148views Education» more  LREC 2010»
13 years 10 months ago
POS Multi-tagging Based on Combined Models
In the POS tagging task, there are two kinds of statistical models: one is generative model, such as the HMM, the others are discriminative models, such as the Maximum Entropy Mod...
Yan Zhao, Gertjan van Noord
ICA
2010
Springer
13 years 9 months ago
Probabilistic Latent Tensor Factorization
We develop a probabilistic modeling framework for multiway arrays. Our framework exploits the link between graphical models and tensor factorization models and it can realize any ...
Y. Kenan Yilmaz, A. Taylan Cemgil
TMM
2002
123views more  TMM 2002»
13 years 8 months ago
Object tracking using the Gabor wavelet transform and the golden section algorithm
This paper presents an object tracking method for object-based video processing which uses a two-dimensional (2-D) Gabor wavelet transform (GWT) and a 2-D golden section algorithm....
Chao He, Yuan F. Zheng, Stanley C. Ahalt