Machine-learning based statistical data matching and its application to microarray data analysis

• Project/Area Number: 23700165
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Intelligent informatics
• Research Institution: Nagoya Institute of Technology
• Principal Investigator: ICHIRO Takeuchi 名古屋工業大学, 工学(系)研究科(研究院), 准教授 (40335146)
• Project Period (FY): 2011 – 2013
• Project Status: Completed (Fiscal Year 2013)
• Budget Amount: ¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000); Fiscal Year 2013: ¥1,820,000 (Direct Cost: ¥1,400,000、Indirect Cost: ¥420,000); Fiscal Year 2012: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000); Fiscal Year 2011: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
• Keywords: machine learning / bioinformatics / statistics / 機械学習 / マイクロアレイ / 多変量検定 / サポートベクトルマシン

Research Abstract

We developed an algorithm and a software that can be used for evaluating the credibility of the knowledge taken from genome-wide biological data such as DNA expression microarray. Our algorithm is based on machine learning technology and it can compute the credibility of the knowledge efficiently. Our results are useful for evidence-based bio-medical studies.

Research Products

• [Journal Article] Multi-parametric solution-path algorithm for instance-weighted support vector machines (2012)
  • Author(s): M. Karasuyama, N. Harada, M. Sugiyama and I. Takeuchi
  • Journal Title: Machine Learning Volume: vol.88 Pages: 297-330
• [Journal Article] Multi-parametric Solution-path Algorithm for Instance-weighted Support Vector Machines (2012)
  • Author(s): M. Karasuyama, N. Harada, M. Sugiyama, I. Takeuchi
  • Journal Title: Machine Learning Volume: 88 Pages: 297-330
  • Peer Reviewed
• [Journal Article] Nonlinear regularization path for quadratic loss support vector machines (2011)
  • Author(s): M. Karasuyama and I. Takeuchi
  • Journal Title: IEEE Transactions on Neural Networks Volume: vol.22 Pages: 1513-1625
• [Journal Article] Nonlinear Regularization Path for Quadratic Loss Support Vector Machines (2011)
  • Author(s): M.Karasuyama, I.Takeuchi
  • Journal Title: IEEE Transactions on Neural Networks Volume: 22 Issue: 10 Pages: 1613-1625
  • DOI: 10.1109/tnn.2011.2164265
  • Peer Reviewed
• [Presentation] Infinitesimal annealing for training semi-supervised support vector machines (2013)
  • Author(s): K. Ogawa, I. Imamura, I. Takeuchi and M. Sugiyama
  • Organizer: The 30th International Conference on Machine Learning (ICML2013)
• [Presentation] Safe screening of non-support vectors in pathwise SVM computation (2013)
  • Author(s): K. Ogawa, Y. Suzuki and I. Takeuchi
  • Organizer: The 30th International Conference on Machine Learning (ICML2013)
• [Presentation] Parametric task learning (2013)
  • Author(s): I. Takeuchi, T. Hongo, M. Sugiyama and S. Nakajima
  • Organizer: The 27th Annual Conference on Neural Information Processing Systems (NIPS2013)
• [Presentation] Global solver and its efficient approximation for variational Bayesian low-rank subspace clustering (2013)
  • Author(s): S. Nakajima, A. Takeda, S. D. Babacan, M. Sugiyama and I. Takeuchi
  • Organizer: The 27th Annual Conference on Neural Information Processing Systems (NIPS2013)
• [Presentation] Infinitesimal annealing for training semi-supervised support vector machines (2013)
  • Author(s): K. Ogawa, Imamura, I. Takeuchi, M. Sugiyama
  • Organizer: The 30th International Conference on Machine Learning
  • Place of Presentation: Atlanta, USA
• [Presentation] Safe screening of non-support vectors in pathwise SVM computation (2013)
  • Author(s): K. Ogawa, Y. Suzuki, I. Takeuchi
  • Organizer: The 30th International Conference on Machine Learning
  • Place of Presentation: Atlanta, USA
• [Presentation] Global solver and its efficient approximation for variational bayesian low-rank subspace clustering (2013)
  • Author(s): S. Nakajima, A. Takeda, S. D. Babacan, M. Sugiyama and I. Takeuchi
  • Organizer: The 27th Annual Conference on Neural Information Processing Systems
  • Place of Presentation: Reno, USA
• [Presentation] Parametric Task Learning (2013)
  • Author(s): I. Takeuchi, T. Hongo, M. Sugiyama and S. Nakajima
  • Organizer: The 27th Annual Conference on Neural Information Processing Systems
  • Place of Presentation: Reno, USA
• [Presentation] パラメトリック計画法を用いたS3VM の最適化手法に関する一考察 (2012)
  • Author(s): 小川晃平, 竹内一郎, 杉山将
  • Organizer: 電子情報通信学会IBISML 研究会
• [Presentation] パラメトリック計画法を用いたマルチインスタンスSVM (2012)
  • Author(s): 石原直樹, 久留美里織, 竹内一郎
  • Organizer: 電子情報通信学会IBISML 研究会
• [Presentation] Density-difference estimation (2012)
  • Author(s): M. Sugiyama, T. Kanamori, T. Suzuki, M. Plessis, S. Liu and I. Takeuchi
  • Organizer: 26th Annual Conference on Neural Information Processing Systems (NIPS2012)
• [Presentation] Density-Difference Estimation (2012)
  • Author(s): M Sugiyama, T Kanamori, T Suzuki, M Plessis, S Liu, I Takeuchi
  • Organizer: 26th Annual Conference on Neural Information Processing Systems (NIPS2012)
  • Place of Presentation: レノ（アメリカ）
• [Presentation] パラメトリック計画法を用いたS3VMの最適化手法に関する一考察 (2012)
  • Author(s): 小川晃平, 竹内一郎, 杉山将
  • Organizer: 電子情報通信学会IBISML研究会
  • Place of Presentation: 京都
• [Presentation] パラメトリック計画法を用いたマルチインスタンスSVM (2012)
  • Author(s): 石原直樹, 久留美里織, 竹内一郎
  • Organizer: 電子情報通信学会IBISML研究会
  • Place of Presentation: 東京
• [Presentation] Target neighbor consistent feature weighting for nearest neighbor classification (2011)
  • Author(s): I. Takeuchi and M. Sugiyama
  • Organizer: 25th Annual Conference on Neural Information Processing Systems (NIPS2011)
• [Presentation] Target neighbor consistent feature weighting for nearest neighbor classification (2011)
  • Author(s): I. Takeuchi and M Sugiyama
  • Organizer: 25th Annual Conference on Neural Information Processing Systems (NIPS2011)
  • Place of Presentation: グラナダ（スペイン）