論文

• Nakajima, S., Sugiyama, M., & Babacan, D.. Variational Bayesian sparse additive matrix factorization, Machine Learning, vol. 92, no. 2-3, pp. 319-347, 2013.
• Nakajima, S., Sugiyama, M., Babacan, D., &Tomioka, R.. Global analytic solution of fully-observed variational Bayesian matrix factorization, Journal of Machine Learning Research, vol. 14(Jan.), pp. 1-37, 2013.
• Nakajima, S., Sugiyama, M.. Theoretical analysis of Bayesian matrix factorization, Journal of Machine Learnig Research, vol. 12, pp. 2583-2648, 2011.
• SHINICHI NAKAJIMA, SUMIO WATANABE. Variational Bayes Solution of Linear Neural Networks and its Generalization Performance, Neural Computation, Vol. 19, No. 4, pp. 1112-1153, 2007.
• 高松 慎吾, 中島伸一, 渡邊澄夫. 局所化ベイズ学習法, 電子情報通信学会論文誌, Vol. J89-D-II, No. 10, pp. 2260-2268, Dec. 2006.
• SHINICHI NAKAJIMA, SUMIO WATANABE. Generalization Performance of Subspace Bayes Approach in Linear Neural Networks, IEICE Transactions, Vol. E89-D, No. 3, pp. 1128-1138, Feb. 2006.

著書

• 渡邊澄夫, 永尾 太郎, 樺島祥介, 田中利幸, 中島伸一. ランダム行列の数理と科学, 森北出版, Apr. 2014.
• 元田浩, 栗田多喜夫, 樋口知之, 松本裕治, 村田昇, 赤穂昭太郎, 神嶌敏弘, 杉山将, 小野田崇, 池田和司, 鹿島久嗣, 賀沢秀人, 中島伸一, 竹内純一, 持橋大地, 小山聡, 井手剛, 篠田浩一, 山川宏. パターン認識と機械学習（下）ベイズ理論による統計的予測, パターン認識と機械学習・ベイズ理論による統計的予測, 丸善出版, page 433, July 2008.

国際会議発表 (査読有り)

• SHINICHI NAKAJIMA, SUMIO WATANABE. Generalization Error of Automatic Relevance Determination, Proc. of ICANN, pp. 1-10, 2007.
• Shingo Takamatsu, SHINICHI NAKAJIMA, SUMIO WATANABE. Localized Bayes Estimation for Non-identifiable Models, Proc. of International Conference on Neural Information Processing, pp. 650-659, Oct. 2006.
• SHINICHI NAKAJIMA, SUMIO WATANABE. Analytic Solution of Hierarchical Variational Bayes in Linear Inverse Problem, Proc. of International Conference on Artificial Neural Networks, pp. 240-249, Sept. 2006.
• SHINICHI NAKAJIMA, SUMIO WATANABE. Generalization Error and Free Energy of Linear Neural Networks in Variational Bayes Approach, Proc. of ICONIP2005, 2005.
• SHINICHI NAKAJIMA, SUMIO WATANABE. Generalization Error of Linear Neural Networks in an Empirical Bayes Approach, Proc. of IJCAI2005, 2005.

国際会議発表 (査読なし・不明)

• Nakajima, S., Sugiyama, M., Babacan, D.. Sparse additive matrix factorizationfor robust PCA and its generalization., The Forth Asian Conference on Machine Learning (ACML2012), JMLR Workshop and Conference Proceedings, S.C.H.Hoi,W.Buntine(Eds.), vol. 25, pp. 301-316, 2012.
• Nakajima, S., Tomioka, R., Sugiyama, M., Babacan, D.. Perfect dimensionality recovery by variational Bayesian PCA., Neural Information Processing Systems(NIPS2012), Advances in Neural Information Processing Systems 25, P.Bartlett,F.C.N.Pereira,X.J.C.Burges,L.Bottou,K.Q.Weinberger(Eds.), pp. 980-988, 2012.

国内会議発表 (査読なし・不明)

• Nakajima, S., Tomioka, R., Sugiyama, M., & Babacan, D.. On dimensionality recovery guarantee of variational Bayesian PCA., IBIS2012-66, pp. 229-236, 2013.
• Nakajima, S., Sugiyama, M., & Babacan, D.. Foreground/background video separation by segmentaion-based generalized matrix factorization, Meeting on Image Recognition and Understanting 2012, Aug. 2012.

学位論文

• Asymptotic theory of empirical and variational Bayes learning,  Thesis,  Doctor of Science,  Tokyo Institute of Technology,  2006/03/26, 

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