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INFORMATICALT
2011
112views more  INFORMATICALT 2011»
13 years 4 months ago
The Minimum Density Power Divergence Approach in Building Robust Regression Models
It is well known that in situations involving the study of large datasets where influential observations or outliers maybe present, regression models based on the Maximum Likeliho...
Alessandra Durio, Ennio Davide Isaia
INTERSPEECH
2010
13 years 3 months ago
Semi-supervised part-of-speech tagging in speech applications
When no training or adaptation data is available, semisupervised training is a good alternative for processing new domains. We perform Bayesian training of a part-of-speech (POS) ...
Richard Dufour, Benoît Favre
CORR
2011
Springer
182views Education» more  CORR 2011»
13 years 26 days ago
Adaptively Learning the Crowd Kernel
We introduce an algorithm that, given n objects, learns a similarity matrix over all n2 pairs, from crowdsourced data alone. The algorithm samples responses to adaptively chosen t...
Omer Tamuz, Ce Liu, Serge Belongie, Ohad Shamir, A...
ICASSP
2011
IEEE
13 years 24 days ago
Towards robust word discovery by self-similarity matrix comparison
Word discovery is the task of discovering and collecting occurrences of repeating words in the absence of prior acoustic and linguistic knowledge, or training material. The capabi...
Armando Muscariello, Guillaume Gravier, Fré...
ICML
2006
IEEE
14 years 10 months ago
Robust probabilistic projections
Principal components and canonical correlations are at the root of many exploratory data mining techniques and provide standard pre-processing tools in machine learning. Lately, p...
Cédric Archambeau, Michel Verleysen, Nicola...