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M. Yamada

4 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • stat.ML4
same name
  • M. Yamada — 4 papers, h 12
  • M. Yamada — 4 papers, h 10
  • M. Yamada — 3 papers, h 39
  • M. Yamada — 1 paper, h 7
  • M. Yamada — 1 paper, h 3
  • M. Yamada — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedCross-Domain Object Matching with Model Selection

31 citations · 60 across the 4 of their papers we have counts for

collaborators
Showing stat.MLShow all

4 papers · 1 filter

stat.ML2011★ 28 cited

Relative Density-Ratio Estimation for Robust Distribution Comparison

Makoto Yamada, Taiji Suzuki, Takafumi Kanamori +2

Divergence estimators based on direct approximation of density-ratios without going through separate approximation of numerator and denominator densities have been successfully app…

stat.ML2011

Least-Squares Independence Regression for Non-Linear Causal Inference under Non-Gaussian Noise

Makoto Yamada, Masashi Sugiyama, Jun Sese

The discovery of non-linear causal relationship under additive non-Gaussian noise models has attracted considerable attention recently because of their high flexibility. In this pa…

stat.ML2011★ 1 cited

Sufficient Component Analysis for Supervised Dimension Reduction

Makoto Yamada, Gang Niu, Jun Takagi +1

The purpose of sufficient dimension reduction (SDR) is to find the low-dimensional subspace of input features that is sufficient for predicting output values. In this paper, we pro…

stat.ML2010★ 31 cited

Cross-Domain Object Matching with Model Selection

Makoto Yamada, Masashi Sugiyama

The goal of cross-domain object matching (CDOM) is to find correspondence between two sets of objects in different domains in an unsupervised way. Photo album summarization is a ty…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.