450 citations · 1.2k across the 59 of their papers we have counts for
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Nys-Newton: Nyström-Approximated Curvature for Stochastic Optimization
Dinesh Singh, Hardik Tankaria, Makoto Yamada
Second-order optimization methods are among the most widely used optimization approaches for convex optimization problems, and have recently been used to optimize non-convex optimi…
Adversarial Regression with Doubly Non-negative Weighting Matrices
Tam Le, Truyen Nguyen, Makoto Yamada +2
Many machine learning tasks that involve predicting an output response can be solved by training a weighted regression model. Unfortunately, the predictive power of this type of mo…
Fixed Support Tree-Sliced Wasserstein Barycenter
Yuki Takezawa, Ryoma Sato, Zornitsa Kozareva +2
The Wasserstein barycenter has been widely studied in various fields, including natural language processing, and computer vision. However, it requires a high computational cost to…
Re-evaluating Word Mover's Distance
Ryoma Sato, Makoto Yamada, Hisashi Kashima
The word mover's distance (WMD) is a fundamental technique for measuring the similarity of two documents. As the crux of WMD, it can take advantage of the underlying geometry of th…
Computationally Efficient Wasserstein Loss for Structured Labels
Ayato Toyokuni, Sho Yokoi, Hisashi Kashima +1
The problem of estimating the probability distribution of labels has been widely studied as a label distribution learning (LDL) problem, whose applications include age estimation,…
Dynamic Sasvi: Strong Safe Screening for Norm-Regularized Least Squares
Hiroaki Yamada, Makoto Yamada
A recently introduced technique for a sparse optimization problem called "safe screening" allows us to identify irrelevant variables in the early stage of optimization. In this pap…