[1-28]

[1]         白田由香利, 村上朱音, 佐倉環, and 久保山哲二, "コロナ期のグローバル市場の指標変動パターンのクラスタリング," 学習院大学計算機センター年報, vol. 43, 2022.

[2]         白田由香利, "機械学習回帰における Shapley 値の理論説明と事例紹介," presented at the DEIM2022, オンライン, 2022. Available: 動画　https://cms.dbsj.org/deim2022/program/

[3]         K. Yamaguchi, "Feature Importance Analysis in Global Manufacturing Industry," International Journal of Trade, Economics Finance, vol. 13, no. 2, pp. 28-35, 2022.

[4]         Y. Shirota and B. Chakraborty, "Amplitude-Based Time Series Data Clustering Method," Gakushuin Economics Papers, vol. 59, no. 2, 2022.

[5]         A. Murakami, Y. Shirota, and Finance, "Effects of Coronavirus on Vegetable Juice Manufacturers," International Journal of Trade, Economics Finance, vol. 13, no. 2, pp. 42-46, 2022.

[6]         A. Murakami and Y. Shirota, "An Analysis of Coronavirus Effects on Global Automakers," International Journal of Trade, Economics Finance, vol. 13, no. 3, pp. 56-60, 2022.

[7]         保科慧 and 白田由香利, "Shapley値による株価上昇における重要要素の分析 〜 精密機械製造企業のケースについての考察 〜," 信学技報, vol. 121, no. 125 DE2021-1, pp. 5-8, 2021年7月 2021.

[8]         藤巻美舞 and 白田由香利, "Shapley値による株価上昇における重要要素の分析 〜 電気機器製造企業のケースについての考察 〜," 信学技報, vol. 121, no. 125 DE2021-1, pp. 9-12, 2021年7月 2021.

[9]         辻浦衣美 and 白田由香利, "Shapley値による株価上昇における重要要素の分析 〜 自動車製造企業のケースについての考察 〜," 信学技報, vol. 121, no. 125 DE2021-1, pp. 1-4, 2021年7月 2021.

[10]      森田道也, 白田由香利, and 永島正康, "世界の電気機器企業の経営特性分析: Ambidextrous 視点からの AI 的アプローチの可能性を探る," in JOMSA 第 13 回全国研究発表大会, オンライン, 2021: JOMSA.

[11]      Y. Shirota and A. Murakami, "Long-term Time Series Data Clustering of Stock Prices for Portfolio Selection," in 2021 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI), 2021, pp. 1-6: IEEE.

[12]      Y. Shirota, M. Fujimaki, E. Tsujiura, M. Morita, and J. A. D. Machuca, "A SHAP Value-Based Approach to Stock Price Evaluation of Manufacturing Companies," in 2021 4th International Conference on Artificial Intelligence for Industries (AI4I), 2021, pp. 75-78: IEEE.

[13]      Y. Shirota and B. Chakraborty, "Automakers Stock Price Movement Comparison under COVID-19," in 2021 International Conference on Data Analytics for Business and Industry (ICDABI), 2021, pp. 375-379: IEEE.

[14]      A. Murakami and Y. Shirota, "Time-series Clustering of Global Automakers Stock Prices," Information Engineering Express, vol. 7, no. 2, pp. 71-83, 2021.

[15]      M. Morita, Y. Shirota, J. A. D. Machuca, and A.-M. Moreno-Moreno, "Limit to growth: Pairwise comparisons of leading Japanese and global B-to-C companies," in The 13th Annual Conference of Operations Management and Strategy Association 2020, virtual conf., 2021: JOMSA.

[16]      H. Ito, A. Murakami, N. Dutta, Y. Shirota, and B. Chakraborty, "Clustering of ETF Data for Portfolio Selection during Early Period of Corona Virus Outbreak," Gakushuin Journal of Economics, vol. 58, no. 1, pp. 99-114, 2021.

[17]      K. Yamaguchi, Y. Shirota, and M. Morita, "Effects of Political Risks on Stock Prices under Global Operations: A Case Study of US-China Trade Friction," in Proc. of 27th EurOMA 2020, virtual conf., 2020, pp. 582-591: EurOMA.

[18]      K. Yamaguchi and Y. Shirota, "Impacts of US-China trade friction on stock prices: An empirical study of machinery companies," International Journal of Applied Science Engineering, vol. 17, no. 4, pp. 383-391, 2020.

[19]      K. Yamaguchi and Y. Shirota, "Decline Patterns of Stock Prices by Disasters—Case Study of May 2019," International Journal of Trade, Economics Finance, vol. 11, no. 3, pp. 39-44, 2020.

[20]      K. Yamaguchi and Y. Shirota, "Classification of Japanese Electrical Equipment Manufacturing Industry Recovery Patterns after Disasters: Case Study of August 2019," International Journal of Trade, Economics Finance, vol. 11, no. 6, pp. 150-155, 2020.

[21]      K. Yamaguchi, "Intrinsic Meaning of Shapley Values in Regression," in 2020 11th International Conference on Awareness Science and Technology (iCAST), 2020, pp. 1-6: IEEE.

[22]      Y. Shirota, K. Yamaguchi, A. Murakami, and M. Morita, "An analysis of political turmoil effects on stock prices: a case study of US-China trade friction," in Proceedings of the First ACM International Conference on AI in Finance, 2020, pp. 1-7.

[23]      Y. Shirota and M. Morita, "Performance Analysis of Japanese Manufacturing Industry before and after Lehman Shock," International Journal of Trade, Economics Finance, vol. 11, no. 5, pp. 87-91, 2020.

[24]      A. Murakami and Y. Shirota, "Portfolio Construction by Hierarchical Clustering-Stock Prices Analysis of 100 Global Car Manufacturers," 電子情報通信学会技術研究報告, vol. 120, no. 78 (DE2020 1-12), pp. 1-5, 2020.

[25]      A. Murakami and Y. Shirota, "Time Series Analysis of Global Automakers Stock Price Clustering," in 2020 9th International Congress on Advanced Applied Informatics (IIAI-AAI), 2020, pp. 588-591: IEEE.

[26]      M. Morita, J. A. D. Machuca, M. Nagashima, and Y. Shirota, "An future image of adaptive operations driven by digitization," in The 12th Annual Conference of Operations Management and Strategy Association 2020, virtual conf., 2020: JOMSA.

[27]      M. Morita, J. A. D. Machuca, M. Nagashima, and Y. Shirota, "Requisites for the digital transformation：Seeing into value creation processes," in The 12th Annual Conference of Operations Management and Strategy Association 2020, virtual conf., 2020: JOMSA.

[28]      S. Kaneko, N. Oyu, and Y. Shirota, "Analysis of Key Factors in Corporate Growth by XGBoost-Case Study of Electrical Manufacturing Industries," IEICE Technical Report IEICE Tech. Rep., vol. 120, no. 78, pp. 7-11, 2020.