no code implementations • 22 Jul 2023 • Eisuke Yamagata, Shunsuke Ono
In this paper, we propose a new problem formulation of sparse index tracking using an $\ell_0$-norm constraint that enables easy control of the upper bound on the number of assets in the portfolio.
no code implementations • 13 Feb 2022 • Eisuke Yamagata, Shunsuke Ono
We propose a time-varying graph signal recovery method for estimating the true time-varying graph signal from observations that are corrupted by missing values, unknown position outliers, and some random noise.
2 code implementations • 21 Jan 2021 • Hirokatsu Kataoka, Kazushige Okayasu, Asato Matsumoto, Eisuke Yamagata, Ryosuke Yamada, Nakamasa Inoue, Akio Nakamura, Yutaka Satoh
Is it possible to use convolutional neural networks pre-trained without any natural images to assist natural image understanding?
no code implementations • 19 Jan 2021 • Nakamasa Inoue, Eisuke Yamagata, Hirokatsu Kataoka
Our main idea is to initialize the network parameters by solving an artificial noise classification problem, where the aim is to classify Perlin noise samples into their noise categories.