Relative Density-Ratio Estimation for Robust Distribution Comparison

DOI10.1162/NECO_a_00442zbMath1414.62115arXiv1106.4729OpenAlexW2101895600WikidataQ44657040 ScholiaQ44657040MaRDI QIDQ5378219

Taiji Suzuki, Makoto Yamada, Takafumi Kanamori, Masashi Sugiyama, Hirotaka Hachiya

Publication date: 12 June 2019

Published in: Neural Computation (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1106.4729

Mathematics Subject Classification ID

Nonparametric estimation (62G05)

Related Items

Density-Difference Estimation, Direct Learning of Sparse Changes in Markov Networks by Density Ratio Estimation, Optimal adaptive estimation of the relative density

Uses Software

• LIBSVM
• bootstrap

Cites Work

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• Direct importance estimation for covariate shift adaptation
• Fast rates for support vector machines using Gaussian kernels
• Improving predictive inference under covariate shift by weighting the log-likelihood function
• Weak convergence and empirical processes. With applications to statistics
• Least-squares two-sample test
• Estimating the Support of a High-Dimensional Distribution
• Least-Squares Independent Component Analysis
• Input-dependent estimation of generalization error under covariate shift
• Asymptotic Statistics
• Estimating Divergence Functionals and the Likelihood Ratio by Convex Risk Minimization
• Convex Analysis
• Theory of Reproducing Kernels
• On Information and Sufficiency
• Soft margins for AdaBoost