activity
20182022
most citedAdaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search

50 citations · 50 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG2022

Probability Distribution on Rooted Trees

Yuta Nakahara, Shota Saito, Akira Kamatsuka +1

The hierarchical and recursive expressive capability of rooted trees is applicable to represent statistical models in various areas, such as data compression, image processing, and…

cs.IT2021

An Efficient Bayes Coding Algorithm for the Non-Stationary Source in Which Context Tree Model Varies from Interval to Interval

Koshi Shimada, Shota Saito, Toshiyasu Matsushima

The context tree source is a source model in which the occurrence probability of symbols is determined from a finite past sequence, and is a broader class of sources that includes…

cs.LG201950 cited

Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search

Youhei Akimoto, Shinichi Shirakawa, Nozomu Yoshinari +3

High sensitivity of neural architecture search (NAS) methods against their input such as step-size (i.e., learning rate) and search space prevents practitioners from applying them…

cs.LG2018

Parameterless Stochastic Natural Gradient Method for Discrete Optimization and its Application to Hyper-Parameter Optimization for Neural Network

Kouhei Nishida, Hernan Aguirre, Shota Saito +2

Black box discrete optimization (BBDO) appears in wide range of engineering tasks. Evolutionary or other BBDO approaches have been applied, aiming at automating necessary tuning of…

cs.IT2018

Non-Asymptotic Fundamental Limits of Guessing Subject to Distortion

Shota Saito, Toshiyasu Matsushima

This paper investigates the problem of guessing subject to distortion, which was introduced by Arikan and Merhav. While the primary concern of the previous study was asymptotic ana…