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» Robust estimation of gaussian mixtures from noisy input data
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UAI
2000
13 years 9 months ago
Utilities as Random Variables: Density Estimation and Structure Discovery
Decision theory does not traditionally include uncertainty over utility functions. We argue that the a person's utility value for a given outcome can be treated as we treat o...
Urszula Chajewska, Daphne Koller
TASLP
2011
13 years 2 months ago
Advances in Missing Feature Techniques for Robust Large-Vocabulary Continuous Speech Recognition
— Missing feature theory (MFT) has demonstrated great potential for improving the noise robustness in speech recognition. MFT was mostly applied in the log-spectral domain since ...
Maarten Van Segbroeck, Hugo Van Hamme
ICDM
2006
IEEE
145views Data Mining» more  ICDM 2006»
14 years 1 months ago
Stability Region Based Expectation Maximization for Model-based Clustering
In spite of the initialization problem, the ExpectationMaximization (EM) algorithm is widely used for estimating the parameters in several data mining related tasks. Most popular ...
Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...
MOBIHOC
2009
ACM
14 years 8 months ago
Fault tolerant target tracking in sensor networks
In this paper, we present a Gaussian mixture model based approach to capture the spatial characteristics of any target signal in a sensor network, and further propose a temporally...
Min Ding, Xiuzhen Cheng
ECCV
2004
Springer
14 years 8 months ago
Evaluation of Robust Fitting Based Detection
Low-level image processing algorithms generally provide noisy features that are far from being Gaussian. Medium-level tasks such as object detection must therefore be robust to out...
Sio-Song Ieng, Jean-Philippe Tarel, Pierre Charbon...