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» Selective use of multiple entropy models in audio coding
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JMLR
2006
156views more  JMLR 2006»
13 years 7 months ago
Large Scale Multiple Kernel Learning
While classical kernel-based learning algorithms are based on a single kernel, in practice it is often desirable to use multiple kernels. Lanckriet et al. (2004) considered conic ...
Sören Sonnenburg, Gunnar Rätsch, Christi...
ICASSP
2011
IEEE
12 years 11 months ago
Estimation of ordinal approach-avoidance labels in dyadic interactions: Ordinal logistic regression approach
Behavioral Signal Processing aims at automating behavioral coding schemes such as those prevalent in psychology and mental health research. This paper describes methods to quantif...
Viktor Rozgic, Bo Xiao, Athanasios Katsamanis, Bri...
WICOMM
2008
116views more  WICOMM 2008»
13 years 7 months ago
Arrayed MC-CDMA reception in space-time diffused multipath vector channels
Multi-Carrier Code Division Multiple Access (MC-CDMA) is a modulation scheme that combines the advantages of OFDM and CDMA to provide robustness against frequency selectivity in w...
Farrukh Rashid, Athanassios Manikas
JMLR
2011
192views more  JMLR 2011»
13 years 2 months ago
Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
Paramveer S. Dhillon, Dean P. Foster, Lyle H. Unga...
CVPR
2012
IEEE
11 years 10 months ago
See all by looking at a few: Sparse modeling for finding representative objects
We consider the problem of finding a few representatives for a dataset, i.e., a subset of data points that efficiently describes the entire dataset. We assume that each data poi...
Ehsan Elhamifar, Guillermo Sapiro, René Vid...