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ICASSP
2009
IEEE
14 years 2 months ago
Small-group learning projects to make signal processing more appealing: From speech processing to OFDMA synchronization
Whereas lecturing is the most widely used mode of instruction, we have explored small-group learning projects to make signal processing more appealing at the University and in Eng...
G. Ferre, Audrey Giremus, Eric Grivel
PAMI
2007
202views more  PAMI 2007»
13 years 6 months ago
Weighted Graph Cuts without Eigenvectors A Multilevel Approach
—A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods....
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
NIPS
1994
13 years 8 months ago
A Non-linear Information Maximisation Algorithm that Performs Blind Separation
A new learning algorithmis derived which performs online stochastic gradient ascent in the mutual informationbetween outputs and inputs of a network. In the absence of a priori kn...
Anthony J. Bell, Terrence J. Sejnowski
PR
2006
164views more  PR 2006»
13 years 7 months ago
Locally linear metric adaptation with application to semi-supervised clustering and image retrieval
Many computer vision and pattern recognition algorithms are very sensitive to the choice of an appropriate distance metric. Some recent research sought to address a variant of the...
Hong Chang, Dit-Yan Yeung
FSMNLP
2008
Springer
13 years 8 months ago
Learning with Weighted Transducers
Weighted finite-state transducers have been used successfully in a variety of natural language processing applications, including speech recognition, speech synthesis, and machine ...
Corinna Cortes, Mehryar Mohri