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AUSDM
2007
Springer
145views Data Mining» more  AUSDM 2007»
15 years 3 months ago
Discovering Frequent Sets from Data Streams with CPU Constraint
Data streams are usually generated in an online fashion characterized by huge volume, rapid unpredictable rates, and fast changing data characteristics. It has been hence recogniz...
Xuan Hong Dang, Wee Keong Ng, Kok-Leong Ong, Vince...
79
Voted
CVIU
2008
82views more  CVIU 2008»
14 years 9 months ago
Shape matching and registration by data-driven EM
In this paper, we present an efficient and robust algorithm for shape matching, registration, and detection. The task is to geometrically transform a source shape to fit a target ...
Zhuowen Tu, Songfeng Zheng, Alan L. Yuille
62
Voted
DSN
2000
IEEE
15 years 1 months ago
On the Quality of Service of Failure Detectors
ÐWe study the quality of service (QoS) of failure detectors. By QoS, we mean a specification that quantifies 1) how fast the failure detector detects actual failures and 2) how we...
Wei Chen, Sam Toueg, Marcos Kawazoe Aguilera
ICPR
2010
IEEE
15 years 4 months ago
Bayesian Inference for Nonnegative Matrix Factor Deconvolution Models
In this paper we develop a probabilistic interpretation and a full Bayesian inference for non-negative matrix deconvolution (NMFD) model. Our ultimate goal is unsupervised extract...
Serap Kirbiz, Ali Taylan Cemgil, Bilge Gunsel
ICASSP
2008
IEEE
15 years 4 months ago
Bayesian extensions to non-negative matrix factorisation for audio signal modelling
We describe the underlying probabilistic generative signal model of non-negative matrix factorisation (NMF) and propose a realistic conjugate priors on the matrices to be estimate...
Tuomas Virtanen, Ali Taylan Cemgil, Simon J. Godsi...