Recent Activities

• A prepreint entitled "Adaptive Lasso, Transfer Lasso, and Beyond: An Asymptotic Perspective" is now available on arXiv. (2023/08)

• I became a visiting associate professor at the Institute of Statistical Mathematics. (2021/04)

• We received an outstanding presentation award at IBIS2020. (2021/01)

CV

• 2016-present: Research and Development Center, Toshiba Corporation.

• 2021-present: Visiting Associate Professor, The Institute of Statistical Mathematics.

• 2017-2020: Department of Statistical Science, School of Multidisciplinary Sciences, The Graduate University for Advanced Studies (SOKENDAI). (Ph.D.)

• 2012-2015: Systems Research and Development Center, NS Solutions Corporation.

• 2010-2012: Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo. (M.S.)

• 2008-2010: Department of Mathematical Engineering and Information Physics, Faculty of Engineering, The University of Tokyo. (B.S.)

• 2006-2008: Natural sciences 1, Collage of arts and sciences, The University of Tokyo.

Award

• The 23rd Workshop on Information-Based Induction Sciences (IBIS2020), Outstanding Presentation Award (2020)

• The Graduate University for Advanced Studies (SOKENDAI), School of Multidisciplinary Sciences Dean's Award (2020)

• The Institute of Statistical Mathematics, Outstanding Student Award (2020)

• Tokyo Electric Power Company Holdings, First Electricity Load Forecasting Technology Contest, 1st Prize (2017)

• The Japanese Society for Artificial Intelligence, Field Innovation Award, Gold Prize (2016)

• KDD Cup, 2nd Prize (2015)

• The 1st International Symposium on Innovative Mathematical Modelling, Poster Gold Prize (2011)

Publications

Journal Papers

• Takada, M., Suzuki, T., & Fujisawa, H. (2020). "Independently Interpretable Lasso for Generalized Linear Models". Neural Computation, 32(6), 1168--1221.

• Takada, M., Hori, Y., & Hara, S. (2014). "Comments and Corrections on “Stability of Genetic Regulatory Networks With Time Delay". IEEE Transactions on Circuits and Systems I: Regular Papers, 61(9), 2771--2774.

• Hori, Y., Takada, M., & Hara, S. (2013). "Biochemical oscillations in delayed negative cyclic feedback: Existence and profiles". Automatica, 49(9), 2581--2590.

Conference Papers

• Takada, M., & Fujisawa, H. (2020). "Transfer Learning via $ell_1$ Regularization". Advances in Neural Information Processing Systems (NeurIPS2020), 33, 14266--14277. (Acceptance Rate: 20.1%)

• Ko, M., Inagi, T., Takada, M., & Yano, T. (2019) "Application of Feature Selection Method to Error Factor Extraction of Multifunction Peripheral". In Proceedings of IEEE International Conference on Industrial Engineering and Engineering Management (IEEM2019) (pp. 1043--1047).

• Takada, M., Fujisawa, H., & Nishikawa, T. (2019). "HMLasso: Lasso with High Missing Rate". In Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI2019) (pp.3541--3547). (Acceptance Rate: 17.9%)

• Takada, M., Suzuki, T., & Fujisawa, H. (2018). "Independently Interpretable Lasso: A New Regularizer for Sparse Regression with Uncorrelated Variables". In Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics (AISTATS2018) (pp.454--463). PMLR, 84. (Acceptance Rate: 33.2%)

• Takada, M., Hori, Y., & Hara, S. (2010). "Existence conditions for oscillations in cyclic gene regulatory networks with time delay". IEEE International Conference on Control Applications (pp. 830--835).

Preprint

• Takada, M., & Fujisawa, H. (2023). "Adaptive Lasso, Transfer Lasso, and Beyond: An Asymptotic Perspective". arXiv preprint arXiv:2308.15838.

Japanese publications are excluded.

Presentations

International Conferences

The above publications are excluded. 

• Takada, M., & Fujisawa, H. (2021). "Transfer learning on regression problem". The 4th International Conference on Econometrics and Statistics (EcoSta2021).

• Takada, M., Saiki, S., Sueyoshi, S., Eguchi, H., & Nishikawa, T. (2017). "Intelligent Causal Analysis System for Wafer Quality Control using Sparse Modeling". AEC/APC Symposium Asia 2017.

• Takada, M., & Aihara, K. (2012). "Cholinergic top-down modulation based on the free-energy principle". The Seventeenth International Symposium on Artificial Life and Robotics (AROB2012) (pp. 569--572).

• Takada, M., & Aihara, K. (2011). "Acetylcholine in cortical learning". The 1st International Symposium on Innovative Mathematical Modelling (ISIMM2011). Poster Gold Prize.

Japanese presentations are excluded.

Patents

• Takada, M. (2021). U.S. Patent Application No. 17/185,577.

• Ko, M., Inagi, T., & Takada, M. (2019). U.S. Patent Application No. 16/817,465.

• Takada, M., Fujisawa, H., & Nishikawa, T. (2020). U.S. Patent Application No. 16/296,312.

• Kakimoto, M., Shin, H., Shiga, Y., & Takada, M. (2019). U.S. Patent Application No. 15/915,569.

• Shiga, Y., Shin, H., Kakimoto, M., & Takada, M. (2019). U.S. Patent Application No. 15/918,373.

• Takada, M., & Nishikawa, T. (2018). U.S. Patent Application No. 15/692,796.

• Takada, M., Furukawa, H., Kohno, H., & Kai, R. (2017). U.S. Patent Application No. 15/373,251.

Japanese patents are excluded.

Contact

Please feel free to contact me.

tkdmah [at] gmail.com