
Learning Domain Invariant Representations by Joint Wasserstein Distance Minimization
Domain shifts in the training data are common in practical applications ...
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Robust modal regression with direct logdensity derivative estimation
Modal regression is aimed at estimating the global mode (i.e., global ma...
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Estimating Density Models with Complex Truncation Boundaries
Truncated densities are probability density functions defined on truncat...
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Unified estimation framework for unnormalized models with statistical efficiency
Parameter estimation of unnormalized models is a challenging problem bec...
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Unified efficient estimation framework for unnormalized models
Parameter estimation of unnormalized models is a challenging problem bec...
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Variable Selection for Nonparametric Learning with Power Series Kernels
In this paper, we propose a variable selection method for general nonpar...
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ModeSeeking Clustering and Density Ridge Estimation via Direct Estimation of DensityDerivativeRatios
Modes and ridges of the probability density function behind observed dat...
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Affine Invariant Divergences associated with Composite Scores and its Applications
In statistical analysis, measuring a score of predictive performance is ...
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DensityDifference Estimation
We address the problem of estimating the difference between two probabil...
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A Conjugate Property between Loss Functions and Uncertainty Sets in Classification Problems
In binary classification problems, mainly two approaches have been propo...
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SemiSupervised learning with DensityRatio Estimation
In this paper, we study statistical properties of semisupervised learni...
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Relative DensityRatio Estimation for Robust Distribution Comparison
Divergence estimators based on direct approximation of densityratios wi...
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fdivergence estimation and twosample homogeneity test under semiparametric densityratio models
A density ratio is defined by the ratio of two probability densities. We...
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Condition Number Analysis of Kernelbased Density Ratio Estimation
The ratio of two probability densities can be used for solving various m...
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Takafumi Kanamori
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