Semi-supervised learning with density-ratio estimation
- 9 February 2013
- journal article
- research article
- Published by Springer Nature in Machine Learning
- Vol. 91 (2) , 189-209
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This publication has 17 references indexed in Scilit:
- Statistical analysis of kernel-based least-squares density-ratio estimationMachine Learning, 2011
- Importance Sampling Via the Estimated SamplerBiometrika, 2007
- A paradox concerning nuisance parameters and projected estimating functionsBiometrika, 2004
- Semi-Supervised Learning on Riemannian ManifoldsMachine Learning, 2004
- kernlab- AnS4Package for Kernel Methods inRJournal of Statistical Software, 2004
- Efficient Estimation of Average Treatment Effects Using the Estimated Propensity ScoreEconometrica, 2003
- Improving predictive inference under covariate shift by weighting the log-likelihood functionJournal of Statistical Planning and Inference, 2000
- Inferences for case-control and semiparametric two-sample density ratio modelsBiometrika, 1998
- The relative value of labeled and unlabeled samples in pattern recognition with an unknown mixing parameterIEEE Transactions on Information Theory, 1996
- Estimation of Regression Coefficients When Some Regressors are not Always ObservedJournal of the American Statistical Association, 1994