Discriminative Learning under Covariate Shift with a Single Optimization Problem
Discriminative Learning under Covariate Shift with a Single Optimization Problem
This chapter derives a discriminative model for learning under differing training and test distributions, and is organized as follows. Section 9.2 formalizes the problem setting. Section 9.3 reviews models for different training and test distributions. Section 9.4 introduces the discriminative model, and Section 9.5 describes the joint optimization problem. Primal and kernelized classifiers are derived for various training and test distributions in Sections 9.6 and 9.7. Section 9.8 analyzes the convexity of the integrated optimization problem. Section 9.9 provides empirical results, and Section 9.10 concludes.
Keywords: covariate shift adaptation, training, test distributions, discriminative model, joint optimization, kernelize learning
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