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NIPS
2004
15 years 5 months ago
Semi-supervised Learning via Gaussian Processes
We present a probabilistic approach to learning a Gaussian Process classifier in the presence of unlabeled data. Our approach involves a "null category noise model" (NCN...
Neil D. Lawrence, Michael I. Jordan
ICML
2010
IEEE
15 years 5 months ago
Metric Learning to Rank
We study metric learning as a problem of information retrieval. We present a general metric learning algorithm, based on the structural SVM framework, to learn a metric such that ...
Brian McFee, Gert R. G. Lanckriet
CORR
2008
Springer
63views Education» more  CORR 2008»
15 years 4 months ago
Testing Statistical Hypotheses About Ergodic Processes
We propose a method for statistical analysis of time series, that allows us to obtain solutions to some classical problems of mathematical statistics under the only assumption tha...
Daniil Ryabko, Boris Ryabko
INTERSPEECH
2010
14 years 11 months ago
Can conversational word usage be used to predict speaker demographics?
This work surveys the potential for predicting demographic traits of individual speakers (gender, age, education level, ethnicity, and geographic region) using only word usage fea...
Dan Gillick
INTERSPEECH
2010
14 years 11 months ago
Semi-supervised training of Gaussian mixture models by conditional entropy minimization
In this paper, we propose a new semi-supervised training method for Gaussian Mixture Models. We add a conditional entropy minimizer to the maximum mutual information criteria, whi...
Jui-Ting Huang, Mark Hasegawa-Johnson