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ECSQARU
2005
Springer
15 years 7 months ago
Default Clustering from Sparse Data Sets
Categorization with a very high missing data rate is seldom studied, especially from a non-probabilistic point of view. This paper proposes a new algorithm called default clusterin...
Julien Velcin, Jean-Gabriel Ganascia
ICPR
2006
IEEE
16 years 3 months ago
Learning Wormholes for Sparsely Labelled Clustering
Distance functions are an important component in many learning applications. However, the correct function is context dependent, therefore it is advantageous to learn a distance f...
Eng-Jon Ong, Richard Bowden
TASLP
2008
120views more  TASLP 2008»
15 years 1 months ago
Rapid Speaker Adaptation Using Clustered Maximum-Likelihood Linear Basis With Sparse Training Data
Abstract-- Speaker space based adaptation methods for automatic speech recognition have been shown to provide significant performance improvements for tasks where only a few second...
Yun Tang, Richard Rose
CORR
2011
Springer
191views Education» more  CORR 2011»
14 years 9 months ago
A Message-Passing Receiver for BICM-OFDM over Unknown Clustered-Sparse Channels
We propose a factor-graph-based approach to joint channel-estimationand-decoding of bit-interleaved coded orthogonal frequency division multiplexing (BICM-OFDM). In contrast to ex...
Philip Schniter