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ICASSP
2010
IEEE
13 years 8 months ago
Power law discounting for n-gram language models
We present an approximation to the Bayesian hierarchical PitmanYor process language model which maintains the power law distribution over word tokens, while not requiring a comput...
Songfang Huang, Steve Renals
ASPDAC
2000
ACM
102views Hardware» more  ASPDAC 2000»
14 years 29 days ago
A hybrid approach for core-based system-level power modeling
Reducing power consumption has become a key goal for systemon-a-chip (SOC) designs. Fast and accurate power estimation is needed early in the design process, since power reduction...
Tony Givargis, Frank Vahid, Jörg Henkel
JCIT
2010
156views more  JCIT 2010»
13 years 3 months ago
Intelligent Monitoring Approach for Pipeline Defect Detection from MFL Inspection
Artificial Neural Networks(ANNS) have top level of capability to progress the estimation of cracks in metal tubes. The aim of this paper is to propose an algorithm to identify mod...
Saeedreza Ehteram, Seyed Zeinolabedin Moussavi, Mo...
CIKM
2000
Springer
14 years 29 days ago
Dimensionality Reduction and Similarity Computation by Inner Product Approximations
—As databases increasingly integrate different types of information such as multimedia, spatial, time-series, and scientific data, it becomes necessary to support efficient retri...
Ömer Egecioglu, Hakan Ferhatosmanoglu
ICML
2007
IEEE
14 years 9 months ago
Hierarchical Gaussian process latent variable models
The Gaussian process latent variable model (GP-LVM) is a powerful approach for probabilistic modelling of high dimensional data through dimensional reduction. In this paper we ext...
Neil D. Lawrence, Andrew J. Moore