Presentation | 2014-11-17 Target Shift Adaptation for Conditional Density Estimation and Regression Than Duong NGUYEN, PLESSIS Marthinus Christoffel DU, Masashi SUGIYAMA, |
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Abstract(in English) | We consider the problem of domain adaptation under the target shift scenario, where the target marginal distribution p(y) changes between the training and testing phases, while the target-conditioned covariate distribution p(x|y) remains unchanged. Although various methods for mitigating target shift in classification (a.k.a. class-prior change) have been developed so far, few methods can be applied to continuous targets. In this paper, we propose methods of continuous target shift adaptation in regression and conditional density estimation. More specifically, our contribution is a novel importance weight estimator for continuous targets. Through experiments, the usefulness of the proposed methods is demonstrated. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | target shift adaptation / conditional density estimation / regression / importance weight |
Paper # | IBISML2014-55 |
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Committee | IBISML |
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Conference Date | 2014/11/10(1days) |
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Registration To | Information-Based Induction Sciences and Machine Learning (IBISML) |
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Language | ENG |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Target Shift Adaptation for Conditional Density Estimation and Regression |
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Keyword(1) | target shift adaptation |
Keyword(2) | conditional density estimation |
Keyword(3) | regression |
Keyword(4) | importance weight |
1st Author's Name | Than Duong NGUYEN |
1st Author's Affiliation | Department of Computer Science, Tokyo Institute of Technology() |
2nd Author's Name | PLESSIS Marthinus Christoffel DU |
2nd Author's Affiliation | Department of Complexity Science and Engineering, University of Tokyo |
3rd Author's Name | Masashi SUGIYAMA |
3rd Author's Affiliation | Department of Complexity Science and Engineering, University of Tokyo |
Date | 2014-11-17 |
Paper # | IBISML2014-55 |
Volume (vol) | vol.114 |
Number (no) | 306 |
Page | pp.pp.- |
#Pages | 6 |
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