454 citations · 5.5k across the 247 of their papers we have counts for
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Feature Selection via L1-Penalized Squared-Loss Mutual Information
Wittawat Jitkrittum, Hirotaka Hachiya, Masashi Sugiyama
Feature selection is a technique to screen out less important features. Many existing supervised feature selection algorithms use redundancy and relevancy as the main criteria to s…
Density-Difference Estimation
Masashi Sugiyama, Takafumi Kanamori, Taiji Suzuki +3
We address the problem of estimating the difference between two probability densities. A naive approach is a two-step procedure of first estimating two densities separately and the…
Dependence Maximizing Temporal Alignment via Squared-Loss Mutual Information
Makoto Yamada, Leonid Sigal, Michalis Raptis +1
The goal of temporal alignment is to establish time correspondence between two sequences, which has many applications in a variety of areas such as speech processing, bioinformatic…
Semi-Supervised Learning of Class Balance under Class-Prior Change by Distribution Matching
Marthinus Du Plessis, Masashi Sugiyama
In real-world classification problems, the class balance in the training dataset does not necessarily reflect that of the test dataset, which can cause significant estimation bias.…
Artist Agent: A Reinforcement Learning Approach to Automatic Stroke Generation in Oriental Ink Painting
Ning Xie, Hirotaka Hachiya, Masashi Sugiyama
Oriental ink painting, called Sumi-e, is one of the most appealing painting styles that has attracted artists around the world. Major challenges in computer-based Sumi-e simulation…
Information-theoretic Semi-supervised Metric Learning via Entropy Regularization
Gang Niu, Bo Dai, Makoto Yamada +1
We propose a general information-theoretic approach called Seraph (SEmi-supervised metRic leArning Paradigm with Hyper-sparsity) for metric learning that does not rely upon the man…