KOSHI WATANABE 渡部航史

渡部航史 Koshi Watanabe

確率的モデルを用いた機械学習に関する研究に従事。
IEEE Graduate Student Member，電子情報通信学会会員。学士 (工学)。

E-mail: koshi [at] lmd.ist.hokudai.ac.jp

経歴

〇Koshi Watanabe, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama, “SpectralMAP: Approximating data manifold with spectral decomposition,” IEEE Access, vol. 11, pp. 31530-31540, 2023. (2022 IF=3.9) [paper]
〇Koshi Watanabe, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama, “Gaussian Process Decoder with Spectral Mixtures and Locally Estimated Manifold for Data Visualization,” Applied Sciences, vol. 13, no. 8018, pp. 1-16, 2023. (2022 IF=2.7) [paper]

〇Koshi Watanabe, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama, “Learning graph Laplacian from intrinsic patterns via Gaussian process,” IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2023. [paper]
〇Koshi Watanabe, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama, “Summarizing data structures with Gaussian process and robust neighborhood preservation,” European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp.153-173, 2022. (242/932=26%) [paper]
〇Koshi Watanabe, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama, “Distributed label dequantized Gaussian process latent variable model for multi-view data integration,” IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), pp.4643-4647, 2022. [paper]
〇Koshi Watanabe, Keisuke Maeda, Takahiro Ogawa and Miki Haseyama, “Movie rating estimation based on weakly supervised multi-modal latent variable model,” IEEE Global Conference on Consumer Electronics (GCCE), pp.221–222, 2021. [paper]

〇渡部航史, 前田圭介, 小川貴弘, 長谷山美紀, “クラス情報を導入したグラフ表現による教師有り潜在変数モデルの高精度化に関する検討,” 映像情報メディア学会技術報告, vol. 47, no. 6, pp. 233–237, 2023.
〇渡部航史, 前田圭介, 小川貴弘, 長谷山美紀, “自己教師あり学習を導入した潜在変数モデルによる低次元特徴の抽出に関する検討,” 令和3年度電気・情報関係学会北海道支部連合大会, pp. 108–109, 2021.