名古屋大学データ駆動システム研究グループ（竹内・田地研究室）

研究業績

[2023 and After] [2022] [2021] [2020] [2019] [2018] [2017] [2016] [2015] [2014] [2013] [2012] [2011] [2010] [2009] [2008] [2007 and Before]

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2023 and After

[Journal Papers]

Noriaki Hashimoto, Hiroyuki Hanada, Hiroaki Miyoshi, Miharu Nagaishi, Kensaku Sato, Hidekata Hontani, Koichi Ohshima, Ichiro Takeuchi. Multimodal gated mixture of experts using whole slide image and flow cytometry for multiple instance learning classification of lymphoma. Journal of Pathology Informatics (to appear)

Nagaishi M., Miyoshi H., Kugler M., Sato K., Kohno K., Takeuchi M., Yamada K., Hashimoto N., Takeuchi I., Hontani H., Ohshima K. The detection of neoplastic cells by objectivecytomorphological parameters in malignant lymphoma. Laboratory Investigation (to appear)

Yoshida T., Hanada H., Nakagawa K., Taji K., Tsuda K., Takeuchi I. Efficient Model Selection for Predictive Pattern Mining Model by Safe Pattern Pruning. Patterns (to appear)

Das D., Ndiaye E. and Takeuchi I. A Confidence Machine for Sparse High-Order Interaction Model. Stat (to appear)

Fuse Y., Takeuchi K., Nagashima Y., Hashimoto N., Nishiwaki H., Nagata Y., Ohka F., Takeuchi I., Ohno K., Saito R. Deep learning based identification of pituitary adenoma on surgical endoscopic images: a pilot study. Neurosurgical Review (to appear)

Yamaguchi Y., Atsumi T., Kanamori K., Tanibata N., Takeda H., Nakayama M., Karasuyma M., Takeuchi I. Drawing A Materials Map with An Autoencoder for Lithium Ionic Conductors. Scientific Reports (to appear)

Hanada H., Hashimoto N., Taji K. and Takeuchi I. Generalized Low-Rank Update: Model Parameter Bounds for Low-Rank Training Data Modifications. Neural Computation (to appear)

Goto K., Tamehiro N., Yoshida T., Hanada H., Sakuma T., Adachi R., Kondo K., Takeuchi I. Novel Machine Learning Method AllerStat Identifies Statistically Significant Allergen-Specific Patterns in Protein Sequences. Journal of Biological Chemistry Vol.299-6, 104733 (2023) (May, 2023)

Hashimoto N., Takagi Y., Masuda H., Miyoshi H., Kohno K., Nagaishi M., Sato K., Takeuchi M., Furuta T., Kawamoto K., Yamada K., Moritsubo M., Inoue K., Shimasaki Y., Ogura Y., Imamoto T., Mishina T., Tanaka K., Kawaguchi Y., Nakamura S., Ohshima K., Hontani H., Takeuchi I. Case-based Similar Image Retrieval for Weakly Annotated Large Histopathological Images of Malignant Lymphoma Using Deep Metric Learning. Medical Image Analysis vol.85, 102752 (Apr, 2023)

Kato H., Hanada H., Takeuchi I. Safe RuleFit: Learning Optimal Sparse Rule Model by Meta Safe Screening. IEEE Transactions on Pattern Analysis and Machine Intelligence Vol.45-2, pp.2330-2343 (Feb, 2023)

Takagi Y., Hashimoto N., Masuda H., Miyoshi H., Ohshima K., Hontani H., Takeuchi I. Transformer-based Personalized Attention Mechanism for Medical Images with Clinical Records. Journal of Pathology Informatics (Jan 2, 2023)

[Conference Papers]

Shogo Iwazaki, Tomohiko Tanabe, Mitsuru Irie, Shion Takeno, Yu Inatsu. Risk Seeking Bayesian Optimization under Uncertainty for Obtaining Extremum AI&Statistics (AIStats)
(May, 2024)

Yu Inatsu, Shion Takeno, Hiroyuki Hanada, Kazuki Iwata, Ichiro Takeuchi. Bounding Box-based Multi-objective Bayesian Optimization of Risk Measures under Input Uncertainty AI&Statistics (AIStats)
(May, 2024)

Duy Vo Nguyen Le, Hsuan-Tien Lin, Ichiro Takeuchi. CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference AI&Statistics (AIStats)
(May, 2024)

Ozaki R., Ishikawa K., Kanzaki Y., Takeno S., Takeuchi I., Karasuyama M. Multi-objective Bayesian Optimization with Active Preference Learning. Proceedings of AAAI Conference on Artificial Intelligence (AAAI) (Feb, 2024)

Koga R., Kugler M., Yokota T., Ohshima K., Miyoshi H., Nagaishi M., Hashimoto N., Takeuchi I., Hontani H. Modification of DDIM Encoding for Generating Counterfactual Pathology Images of Malignant Lymphoma. Proceedings of International Conference on Computer Vision Theory and Applications (VISAPP) (Feb, 2024)

S. Iwazaki, S. Takeno, T. Tanabe, M. Irie Failure-Aware Gaussian Process Optimization with Regret Bounds Proceedings of Advances in Neural Information Processing Systems 36 (NeurIPS) (Dec, 2023)

Butke J., Hashimoto N., Takeuchi I., Miyoshi H., Oshima K., Sakuma J. Mixing Histopathology Prototypes into Robust Slide-Level Representations for Cancer Subtyping Machine Learning in Medical Imaging (MLMI) (Oct, 2023)

S. Takeno, Y, Inatsu, M. Karasuyama Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds Proceedings of The 40th International Conference on Machine Learning (ICML) (Jul, 2023)

S. Takeno, M, Nomura, M. Karasuyama Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes Proceedings of The 40th International Conference on Machine Learning (ICML) (Jul, 2023)

Ishibashi H., Karasuyama M., Takeuchi I., Hino H. A Stopping Criterion for Bayesian Optimization by The Gap of Expected Minimum Simple Regrets Proceedings of The International Conference on AI and Statistics (AISTATS) (Apr, 2023)

Miwa D., Duy V.N.L., Takeuchi I. Valid P-Value for Deep Learning-driven Salient Region Proceedings of The International Conference on Learning Representation (ICLR) (May, 2023)

Koga R., Kugler M., Yokota T., Ohshima K., Miyoshi H., Nagaishi M., Hashimoto N., Takeuchi I., Hontani H. Generation of Counterfactual Images to Construct Criteria for Quantitatively Evaluating Subtypes in Malignant Lymphoma. Proceedings of The International Forum on Medical Imaging in Asia (IFMIA) (Jan, 2023)

Koide S., Kugler M., Yokota T., Ohshima K., Miyoshi H., Nagaishi M., Hashimoto N., Takeuchi I., Hontani H. Construction of Classifier for malignant lymphoma nuclei using label propagation Proceedings of The International Forum on Medical Imaging in Asia (IFMIA) (Jan, 2023)

Tanaka H., Hashimoto N., Yokota T., Kugler M., Ohshima K., Miyoshi H., Nagaishi M., Takeuchi I., Hontani H. Graph neural network for identification of malignant lymphoma subtypes and class activation visualization of cell tissue anomality. Proceedings of The International Forum on Medical Imaging in Asia (IFMIA) (Jan, 2023)

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2022

[Journal Papers]

Ndiaye E., Takeuchi I. Root-finding Approaches for Computing Conformal Prediction Set. Machine Learning (Nov 23, 2022)

Suzuki K., Tange M., Yamaguchi R., Hanada H., Mukai S., Sato T., Tanaka T., Akashi T., Kadomatsu K., Miida T., Takeuchi I., Sekido Y., Murakami-Tonami Y. SMG6 Regulates DNA Damage and Cell Survival in Hippo Pathway Kinase LATS2-Inactivated Malignant Mesothelioma. Cell Death Discovery (Nov 5, 2022)

Duy V.N.L., Takeuchi I. More Powerful Conditional Selective Inference for Generalized Lasso by Parametric Programming. Journal of Machine Learning Research (Nov, 2022)

Kusakawa S., Takeno S., Inatsu Y., Kutsukake K., Iwazaki S., Nakano T., Ujihara T., Karasuyama M., Takeuchi I. Bayesian Optimization for Cascade-type Multistage Processes. Neural Computation vol.34(12), pp.2408–2431. (Nov 8, 2022)

Fukuda H., Kusakawa, S., Nakano, K., Tanibata, N., Takeda H., Nakayama, M., Karasuyama M., Takeuchi I., Natorie T., Onoe Y. Bayesian optimisation with transfer learning for NASICON-type solid electrolytes for all-solid-state Li-metal batteries. RSC Advances (Oct 26, 2022)

Lempidakis E., Shepard E.L.C, Ross A.N., Matsumoto S., Koyama S., Takeuchi I., Yoda K. Pelagic seabirds reduce risk by flying into the eye of the storm. Proceedings of National Academy of Science (PNAS) vol.119(41), e2212925119 (Oct 4, 2022)

Takeno S., Fukuoka H., Tsukada Y., Koyama T., Shiga M., Takeuchi I., Karasuyama M. A Generalized Framework of Multi-fidelity Max-value Entropy Search through Joint Entropy. Neural Computation (Sep 12, 2022)

Nakayama M., Nakano K., Harada M., Tanibata N., Takeda H., Noda Y., Kobayashi R., Karasuyama M., Takeuchi I., Kotobuki M. Na Superionic Conductor-Type LiZr2(PO4)3 as a Promising Solid Electrolyte for Use in All-Solid-State Li Metal Batteries. Chemical Communications (Aug 28, 2022)

Tsukurimichi T., Inatsu Y., Duy V.N.L., Takeuchi I. Conditional Selective Inference for Robust Regression and Outlier Detection using Piecewise-Linear Homotopy Continuation. Annals of Institute of Statistical Mathematics (Aug 27, 2022)

Duy V.N.L., Takeuchi I. Exact Statistical Inference for the Wasserstein Distance by Selective Inference. Annals of Institute of Statistical Mathematics vol.75, pp.127–157 (2023)

Ohno K., Nishiwaki H., Ito M., Hamaguchi T., Maeda T., Kashihara K., Tsuboi Y., Ueyama J., Yoshida T., Hanada H., Takeuchi I., Katsuno M., hirayama M. Short chain fatty acids-producing and mucin-degrading intestinal bacteria predict the progression of early Parkinson's disease. npj Parkinson's Disease (Jun 01, 2022)

Hashimoto N., Ko K., Yokota T., Kohno K., Nakaguro M., Nakamura S., Takeuchi I., Hontani H. Subtype Classification of Malignant Lymphoma Using Immunohistochemical Staining Pattern. International Journal of Computer Assisted Radiology and Surgery (Feb 11, 2022)

Atsumi T, Sato K., Yamaguchi Y., Hamaie M., Yasuda R., Tanibata N., Takeda H., Nakayama M., Karasuyama M., Takeuchi I. Chemical composition data-driven machine-learning prediction for phase stability and materials properties of inorganic crystalline solids. Physica Status Solidi B (Feb 03, 2022)

[Conference Papers]

Duy V.N.L., Iwazaki S., Takeuchi I. Quantifying Statistical Significance of Neural Network-based Image Segmentation by Selective Inference. Proceedings of 36th Conference on Neural Information Processing Systems (NeurIPS) (Dec, 2022)

Inatsu Y., Takeno S., Karasuyama M., Takeuchi I. Bayesian Optimization for Distributionally Robust Chance-constrained Problem. Proceedings of International Conference on Machine Learning (ICML) (Jul, 2022)

Das D., Duy V.N.L., Hanada H., Tsuda K., Takeuchi I. Fast and More Powerful Selective Inference for Sparse High-order Interaction Model. Proceedings of AAAI Conference on Artificial Intelligence (AAAI) (Jul, 2022)

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2021

[Journal Papers]

Iwazaki S., Inatsu Y., Takeuchi I. Bayesian Quadrature Optimization for Probability Threshold Robustness Measure Neural Computation (2021)

Yoshida T., Takeuchi I, Karasuyama M. Distance Metric Learning for Graph Structured Data. Machine Learning (2021)

Bunker R., Fujii K., Hanada H., Takeuchi I. Supervised Sequential Pattern Mining of Event Sequences in Sport to Identify Important Patterns of Play: An Application to Rugby Union. Plos One (2021)

Duy V.N.L., Sakuma T., Ishiyama T., Toda H., Arai K., Karasuyama M., Okubo Y., Sunaga M., Hanada H., Tabei Y., Takeuchi I. Stat-DSM: Statistically Discriminative Sub-trajectory Mining with Multiple Testing Correction. IEEE Transactions on Knowledge and Data Engineering (2021)

Yang Z., Suzuki S., Tanibata N., Takeda H., Nakayama M., Karasuyama M., Takeuchi I. An Efficient Experimental Search for Discovering Fast Li Ion Conductor from Perovskite-type LixLa(1-x)/3NbO3 (LLNO) Solid State Electrolyte Using Bayesian Optimization. The Journal of Physical Chemistry C (2021)

Ueno K., Ichikawa K., Sato K., Sugita D., Yotsuhashi S., Takeuchi I. Robust and efficient calculation of activation energy by automated path search and density functional theory. Physical Review Materials (2021)

Inoue K., Karasuyama M., Nakamura R., Konno M., Yamada D., Mannen K., Nagata T., Inatsu Y., Yawo H., Yura K., Béjà O., Kandori H., Takeuchi I. Exploration of natural red-shifted rhodopsins using a machine learning-based Bayesian experimental design. Communication Biology (2021)

Suzumura S., Nakagawa K., Umezu Y., Tsuda K., Takeuchi I. Selective inference for high-order interaction features selected in a stepwise manner. IPSJ Transactions on Bioinformatics (2021)

[Conference Papers]

Sugiyama K., Duy V.N.L., Takeuchi I. More Powerful and General Selective Inference for Stepwise Feature Selection using Homotopy Method. Proceedings of International Conference on Machine Learning (ICML) (2021)

Inatsu Y., Iwazaki S., Takeuchi I. Active Learning for Distributionally Robust Level-Set Estimation. Proceedings of International Conference on Machine Learning (ICML) 2021

Iwazaki S., Inatsu Y., Takeuchi I. Mean-Variance Analysis in Bayesian Optimization under Uncertainty. The 24th International Conference on Artifical Intelligence and Statistics (AISTATS2021). 2021

Duy V.N.L., Takeuchi I. Parametric Programming Approach for More Powerful and General Lasso Selective Inference. The 24th International Conference on Artifical Intelligence and Statistics (AISTATS2021). 2021

Koga R., Hashimoto N., Yokota T., Nakaguro M., Kohno K., Nakamura S., Takeuchi I., Hontani H. Detection of DLBCL regions in H&E stained whole slide pathology images using Bayesian U-Net Proceedings of International Forum on Medical Imaging in Asia (2021)

Koga R., Hashimoto N., Yokota T., Nakaguro M., Kohno K., Nakamura S., Takeuchi I., Hontani H. Stain transfer for automatic annotation of malignant lymphoma regions in H&E stained whole slide histopathology images Proceedings Volume 11792, International Forum on Medical Imaging in Asia (2021)

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2020

[Journal Papers]

Osada K., Kutsukake K., Yamamoto J., Yamashita S., Kodera T., Nagai Y., Horikawa T. Matsui K. Takeuchi I., Ujihara T. Adaptive Bayesian optimization for epitaxial growth of Si thin films under various constraints. Materials Today Communication (2020)

Iwazaki S., Inatsu Y., Takeuchi I. Bayesian Experimental Design for Finding Reliable Level Set under Input Uncertainty IEEE Access (2020)

Inatsu Y., Karasuyama M., Inoue K., Takeuchi I. Active learning for level set estimation under input uncertainty and its extensions. Neural Computation (2020)

Harada M., Takeda H., Suzuki S., Nakano K., Tanibata N., Nakayama M., Karasuyama M., Takeuchi I. Bayesian-optimization-guided Experimental Search of NASICON-type Solid Electrolytes for All-solid-state Li-ion Batteries. Journal of Materials Chemistry A (2020)

Inatsu Y., Karasuyama M., Inoue K., Kandori H., Takeuchi I. Active Learning of Bayesian Linear Models with High Dimensional Binary Features by Parameter Confidence-Region Estimation. Neural Computation (2020)

Inatsu Y., Sugita D., Toyoura K., Takeuchi I. Active Learning for Enumerating Local Minima Based on Gaussian Process Derivatives. Neural Computation (2020)

Shinjo K., Hara K., Nagae G., Umeda T., Katsushima K., Suzuki M., Murofushi Y., Umezu Y., Takeuchi I., Takahashi S., Okuno Y., Matsuo K., Ito H., Tajima S., Aburatani H., Yamao K., Kondo Y. A Novel Sensitive Detection Method for DNA Methylation in Circulating Free DNA of Pancreatic Cancer. Plos One (2020)

Toyoura K., Fujii T., Kanamori K., Takeuchi I. A Sampling Strategy in Efficient Potential Energy Surface Mapping for Predicting Atomic Diffusivity in Crystals by Machine Learning. Physical Review B (2020)

Nakano K., Noda Y., Tanibata N., Nakayama M., Kobayashi R., Takeuchi I. Exhaustive and Informatics-Aided Search for Fast Li-Ion Conductor with NASICON-Type Structure Using Material Simulation and Bayesian Optimization. APL Materials (2020)

[Conference Papers]

Duy V.N.L., Toda H., Sugiyama R., Takeuchi I. Computing Valid p-value for Optimal Changepoint by Selective Inference using Dynamic Programming. Proceedings of 34th Conference on Neural Information Processing Systems (NeurIPS). (2020)

Takeno S., Fukuoka H., Tsukada Y., Koyama T., Shiga M., Takeuchi I., Karasuyama M. Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization. Proceedings of International Conference on Machine Learning (ICML) (2020)

Tanizaki K., Hashimoto N., Inatsu Y., Hontani H., Takeuchi I. Computing Valid P-values for Image Segmentation by Selective Inference. Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020)

Hashimoto N., Fukushima D., Koga R. Takagi Y., Ko K., Kohno K., Nakaguro M., Nakamura S., Hontani H., Takeuchi I. Multi-scale Domain-adversarial Multiple-instance CNN for Cancer Subtype Classification with Non-annotated Histopathological Images. Proceedings of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2020)

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2019

[Journal Papers]

Yoshida T., Takeuchi I., Karasuyama M. Safe Triplet Screening for Distance Metric Learning. Neural Computation (2019)

Kodera S., Nishimura T., Rashed EA., Hasegawa, K., Takeuchi I. Egawa R., Hirata A. Estimation of heat-related morbidity from weather data: A computational study in three prefectures of Japan over 2013-2018. Environment International (2019)

Umezu Y., Takeuchi I. Selective Inference via Marginal Screening for High Dimensional Classification. Japanese Journal of Statistics and Data Science (2019)

Sakuma T., Nishi K., Kishimoto K., Nakagawa K., Karasuyama M., Umezu Y., Kajioka S., Yamazaki S.J., Kimura K.D., Matsumoto S, Yoda K., Fukutomi M., Shidara H., Ogawa H. and Takeuchi I. Efficient learning algorithm for sparse subsequence pattern-based classification and applications to comparative animal trajectory data analysis. Advanced Robotics (2019)

Yasukochi Y., Sakuma J., Takeuchi I., Kato K., Oguri M., Fujimaki T., Horibe H., Yamada Y. Two novel susceptibility loci for type 2 diabetes mellitus identified by longitudinal exome-wide association studies in a Japanese population. Genomics (2019)

[Conference Papers]

Ndiaye E., Takeuchi I. Computing Full Conformal Prediction Set with Approximate Homotopy Proceedings of 33rd Conference on Neural Information Processing Systems (NeurIPS). (2019)

Vo, DNL, Sakuma T., Ishiyama T., Hiroki T., Arai K., Karasuyama M., Okubo Y., Sunaga M., Tabei Y., Takeuchi I. Statistically Discriminative Sub-trajectory Mining with Multiple Testing Correction. Proceedings of International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL). (2019)

Yoshida T., Takeuchi I., Karasuyama M. Learning Interpretable Metric between Graphs: Convex Formulation and Computation with Graph Mining. Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD). (2019)

Ndiaye Y., Le T., Fercoq O., Salmon J., Takeuchi I. Safe Grid Search with Optimal Complexity. Proceedings of International Conference on Machine Learning (ICML) (2019)

Yamada M., Wu D., Tsai Y.H.H., Ota H., Salakhutdinov R., Takeuchi I., Fukumizu K. Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator. Proceedings of International Conference on Learning Representation (ICLR) (2019)

Kajioka S., Sakuma T., Takeuchi I. Comparative sequential pattern mining of human trajectory data collected from campus-wide BLE beacon system. Proceedings of IEEE International Conference on Pervasive Computing and Communications Workshop (Percom Workshops). (2019)

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2018

[Journal Papers]

Nakayama M., Kanamori K., Nakano K., Jalem R., Takeuchi I., Yamazaki H. Data-Driven Materials Exploration for Li-ion Conductive Ceramics by Exhaustive and Informatics-Aided Computations. The Chemical Record (2018)

Yonezu T., Tamura T., Takeuchi I., Karasuyama M. Knowledge-transfer-based cost-effective search for interface structures: A case study on fcc-Al [110] tilt grain boundary. Physical Review Materials (2018)

Karasuyama M., Inoue K., Nakamura R., Kandori H., Takeuchi I. >Understanding colour tuning rules and predicting absorption wavelengths of microbial rhodopsins by data-driven machine-learning approach. Scientific Reports (2018)

Hirakawa T., Yamashita T., Tamaki T., Fujiyoshi H., Umezu Y., Takeuchi I., Matsumoto S., Yoda K. Can AI predict animal movements? Filling gaps in animal trajectories using Inverse Reinforcement Learning. Ecosphere (2018)

Yamada Y., Horibe H., Oguri M., Sakuma J., Takeuchi I., Yasukouchi Y., Kato K., Motoji Sawabe. Identification of novel hyper- and hypo-methylated CpG sites and genes associated with atherosclerotic plaque using an epigenome-wide association study. International Journal of Molecular Medicine (2018)

Jalem R., Kanamori K., Takeuchi I., Nakayama M. Yamasaki H., Saito T. Bayesian-driven first-principles calculations for accelerating exploration of fast ion conductors for rechargeable battery application. Scientific Reports (2018)

Kanamori K., Toyoura K., Honda J., Hattori K., Seko A., Karasuyama M., Shitara K., Shiga M., Kuwabara A., Takeuchi I. Exploring a potential energy surface by machine learning for characterizing atomic transport. Physical Review B (2018)

Aoki K., Nakamura H., Suzuki H., Matsuo K., Kataoka K., Shimamura T., Motomura K., Ohka F., Shiina S., Yamamoto T., Nagata Y., Yoshizato T., Mizoguchi M., Abe T., Momii Y., Muragaki Y., Watanabe R., Ito I., Sanada M., Yajima H., Morita N., Takeuchi I., Miyano S., Wakabayashi T., Ogawa S., Natsume A. Prognostic relevance of genetic alterations in diffuse lower-grade gliomas. Neuro-Oncology (2018)

[Conference Papers]

Yoshida T., Takeuchi I., Karasuyama M. Safe Triplet Screening for Distance Metric Learning. Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD). (2018)

Sakuma T., Nishi K., Yamazaki SY., Kimura KD., Matsumoto S., Yoda K., Takeuchi I. Finding discriminative animal behaviors from sequential bio-logging trajectory data. Proceedings of Infernational Conference on Distributed, Ambient and Pervasive Interactions (HCI International) (2018)

Yamada M., Umezu Y., Fukumizu K., Takeuchi I. Post Selection Inference with Kernels. Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS) (2018)

Hanada H., Shibagaki A., Sakuma J., Takeuchi I. Efficiently Monitoring Small Data Modification Effect for Large-Scale Learning in Changing Environment. Proceedings of AAAI Conference on Artificial Intelligence (AAAI) (2018.)

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2017

[Journal Papers]

Yasukouchi Y., Sakuma J., Takeuchi I., Kato K., Oguri M., Fujimaki T., Horibe H., Yamada Y. Longitudinal exome-wide association study to identify genetic susceptibility loci for hypertension in a Japanese population. Experimental \& Molecular Medicine (2017)

Yamada Y., Sakuma J., Takeuchi I., Yasukouchi Y., Kato K., Oguri M., Fujimaki T., Horibe H., Muramatsu M., Sawabe M., Fujiwara Y., Taniguchi Y., Obuchi S., Kawai H., Shinkai S., Mori S., Arai T., Tanaka M.. Identification of TNFSF13, SPATC1L, SLC22A25, and SALL4 as novel susceptibility loci for atrial fibrillation in Japanese individuals by an exome-wide association study. Molecular Medicine Reports (2017)

Tamura T., Karasuyama M., Kobayashi R., Arakawa R., Shiihara Y., Takeuchi I. Fast and scalable prediction of local energy at grain boundaries: machine-learning based modeling of first-principles calculations. Modelling and Simulation in Materials Science and Engineering (2017)

Yamada Y., Sakuma J., Takeuchi I., Yasukouchi Y., Kato K., Oguri M., Fujimaki T., Horibe H., Muramatsu M., Sawabe M., Fujiwara Y., Taniguchi Y., Obuchi S., Kawai H., Shinkai S., Mori S., Arai T., Tanaka M.. Identification of five genetic variants as novel determinants of type 2 diabetes mellitus in Japanese individuals by exome-wide association studies. Oncotarget (2017)

Yamada Y.,Sakuma J., Takeuchi I., Yasukouchi Y., Kato K., Oguri M., Fujimaki T., Horibe H., Muramatsu M., Sawabe M., Fujiwara Y., Taniguchi Y., Obuchi S., Kawai H., Shinkai S., Mori S., Arai T., Tanaka M.. Identification of polymorphisms in 12q24.1, ACAD10, and BRAP as novel genetic determinants of blood pressure in Japanese by exome-wide association studies. Oncotarget (2017)

Yamada Y., Sakuma J., Takeuchi I., Yasukouchi Y., Kato K., Oguri M., Fujimaki T., Horibe H., Muramatsu M., Sawabe M., Fujiwara Y., Taniguchi Y., Obuchi S., Kawai H., Shinkai S., Mori S., Arai T., Tanaka M.. Identification of eight genetic variants as novel determinants for dyslipidemia in Japanese by exome-wide association studies. Oncotarget (2017)

Yamada Y., Sakuma J., Takeuchi I., Yasukouchi Y., Kato K., Oguri M., Fujimaki T., Horibe H., Muramatsu M., Sawabe M., Fujiwara Y., Taniguchi Y., Obuchi S., Kawai H., Shinkai S., Mori S., Arai T., Tanaka M.. Identification of STXBP2 as a novel susceptibility locus for myocardial infarction in Japanese individuals by an exome-wide association study. Oncotarget (2017)

Yamada Y., Sakuma J., Takeuchi I., Yasukouchi Y., Kato K., Oguri M., Fujimaki T., Horibe H., Muramatsu M., Sawabe M., Fujiwara Y., Taniguchi Y., Obuchi S., Kawai H., Shinkai S., Mori S., Arai T., Tanaka M.. Identification of EGFLAM, SPATC1L, and RNASE13 as novel susceptibility loci for aortic aneurysm in Japanese individuals by exome-wide association studies.} International Journal of Molecular Medicine (2017)

Yasukochi Y., Sakuma J., Takeuchi I., Kato K., Oguri M., Fujimaki T., Horibe H., Yamada Y. Identification of CDC42BPG as a novel susceptibility locus for hyperuricemia in a Japanese population. Molecular Genetics and Genomics (2017)

Toyoura K., Hirano D., Seko A., Shiga M., Kuwabara A., Karasuyama M., Shitara K., Takeuchi I. Machine-learning-based selective sampling procedure for identifying the low-energy region in a potential energy surface: a case study on proton conduction in oxides.} Physical Review B (2017)

Suzumura S., Ogawa K., Karasuyama M., Sugiyama M., Takeuchi I. Homotopy continuation approaches for robust SV classification and regression. Machine Learning (2017)

Yamada Y., Sakuma J., Takeuchi I., Yasukouchi Y., Kato K., Oguri M., Fujimaki T., Horibe H., Muramatsu M., Sawabe M., Fujiwara Y., Taniguchi Y., Obuchi S., Kawai H., Shinkai S., Mori S., Arai T., Tanaka M. Identification of C21orf59 and ATG2A as novel determinants of renal function-related traits in Japanese by exome-wide association studies. Oncotarget (2017)

Yamada Y., Sakuma J., Takeuchi I., Yasukouchi Y., Kato K., Oguri M., Fujimaki T., Horibe H., Muramatsu M., Sawabe M., Fujiwara Y., Taniguchi Y., Obuchi S., Kawai H., Shinkai S., Mori S., Arai T., Tanaka M. Identification of six polymorphisms as novel susceptibility loci for ischemic or hemorrhagic stroke by exome-wide association studies. International Journal of Molecular Medicine (2017)

Yamada Y., Sakuma J., Takeuchi I., Yasukouchi Y., Kato K., Oguri M., Fujimaki T., Horibe H., Muramatsu M., Sawabe M., Fujiwara Y., Taniguchi Y., Obuchi S., Kawai H., Shinkai S., Mori S., Arai T., Tanaka M. Identification of rs7350481 at chromosome 11q23.3 as a novel determinant of metabolic syndrome in Japanese individuals by exome-wide association studies. Oncotarget (2017)

[Conference Papers]

Suzumura S., Nakagawa K., Umezu Y., Tsuda K., Takeuchi I. Selective Inference for Sparse High-Order Interaction Models. Proceedings of International Conference on Machine Learning (ICML) (2017)

Kusano K. Takeuchi I. Sakuma J. Privacy-preserving and Optimal Interval Release for Disease Susceptibility. Proceedings of ACM on Asia Conference on Computer and Communications Security (ASIA-CCS) (2017)

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2016

[Journal Papers]

Oguri M., Fujimaki T., Horibe H., Kato K., Matsui K.; Takeuchi I., Yamada Y. Obesity-related changes in clinical parameters and conditions in a longitudinal population-based epidemiological study. Obesity Research \& Clinical Practice (2016)

Murakami-Tonami Y., Ikeda H., Yamagishi R., Inayoshi M., Inagaki S., Kishida S., Komata Y., Koster J., Takeuchi I., Kondo Y., Maeda T., Sekido Y., Murakami H., Kadomatsu K. SGO1 is involved in the DNA damage response in MYCN-amplified neuroblastoma cells. Scientific Reports (2016)

Hijiya N., Tsukamoto Y., Nakada C., Lam Tung N., Kai T., Matsuura K., Shibata K., Inomata M., Uchida T., Tokunaga A., Amada K., Shirao K., Yamada Y., Mori H., Takeuchi I., Seto M., Aoki M., Takekawa M., Moriyama M. Genomic loss of DUSP4 contributes to the progression of intraepithelial neoplasm of pancreas to invasive carcinoma. Cancer Research (2016)

Shimada K, Shimada S, Sugimoto K, Nakatochi M, Suguro M, Hirakawa A, Hocking TD, Takeuchi I, Tokunaga T, Takagi Y, Sakamoto A, Aoki T, Naoe T, Nakamura S, Hayakawa F, Seto M, Tomita A, Kiyoi H. Development and analysis of patient-derived xenograft mouse models in intravascular large B-cell lymphoma. Leukemia 201(6)

[Conference Papers]

Takada T., Hanada H., Yamada Y., Sakuma J., Takeuchi I. Secure Approximation Guarantee for Cryptographically Private Empirical Risk Minimization. Proceedings of Asian Conference on Machine Learning (ACML) (2016)

Nakagawa K., Suzumura S., Karasuyama M., Tsuda K., Takeuchi I. Safe Pattern Pruning: An Efficient Approach for Predictive Pattern Mining. Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) (2016)

Shibagaki A., Karasuyama M., Hatano K., Takeuchi I. Simultaneous safe screening of features and samples in doubly sparse modeling. Proceedings of International Conference on Machine Learning (ICML) (2016)

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2015

[Journal Papers]

Yamada Y., Kota Matsui, Takeuchi I., Fujimaki T.. Association of genetic variants with dyslipidemia and chronic kidney disease in a longitudinal population-based genetic epidemiological study. International Journal of Molecular Medicine (2015)

Yamada Y., Kota Matsui, Takeuchi I., Fujimaki T. Association of genetic variants with coronary artery disease and ischemic stroke in a longitudinal population-based genetic epidemiological study. Biomedical Reports (2015)

Yamada Y., Kota Matsui, Takeuchi I., Oguri M., Fujimaki T. Association of genetic variants of the alpha-kinase 1 gene with type 2 diabetes mellitus in a longitudinal population-based genetic epidemiological study. Biomedical Reports (2015)

Yamada Y., Kota Matsui, Takeuchi I., Oguri M., Fujimaki T.. Association of genetic variants with hypertension in a longitudinal population-based genetic epidemiological study. International Journal of Molecular Medicine (2015)

Narimatsu T., Matsuura K., Nakada C., Tsukamoto Y., Hijiya N., Kai T., Inoue T., Uchida T., Nomura T., Sato F., Seto M., Takeuchi I., Mimata H., Moriyama M. Downregulation of NDUFB6 due to 9p24.1-p13.3 loss is implicated in metastatic clear cell renal cell carcinoma. Cancer Medicine (2015)

[Conference Papers]

Shibagaki A., Suzuki Y., Karasuyama M., Takeuchi I. Regularization Path of Cross-Validation Error Lower Bounds. Proceedings of Neural Information Processing Systems (NIPS) (2015)

Okumura S., Suzuki Y., Takeuchi I. Quick Sensitivity Analysis for Incremental Data Modification and Its Application to Leave-one-out CV in Linear Classification Problems. Proceedings of ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) (2015)

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2014

[Journal Papers]

Tanahashi K., Natsume A., Ohka F., Momota H., Kato A., Motomura K., Watabe N., Muraishi S., Nakahara H., Saito Y., Takeuchi I., Wakabayashi T. Assessment of tumor cells in a mouse model of diffuse infiltrative glioma by Raman spectroscopy. BioMed Research International (2014)

Suguro M., Yoshida N., Umino A., Kato H., Tagawa H., Nakagawa M., Fukuhara N., Karnan S., Takeuchi I, Hocking TD., Arita K., Karube K., Tsuzuki S., Nakamura S., Kinoshita T., Seto M. Clonal heterogeneity of lymphoid malignancies correlates with poor prognosis. Cancer Science (2014)

Sasaki H., Takeuchi I., Okada M., Sawada R., Kanie K., Kiyota Y., Honda H., Kato R. Label-free morphology-based prediction of multiple differentiation potentials of human mesenchymal stem cells for early evaluation of intact cells. PLoS One (2014)

Isu N., Hasegawa T., Takeuchi I., Morimoto A. Quantitative analysis of time-course development of motion sickness by in-vehicle video watching. Displays (2014)

Guo Y., Takeuchi I., Karnan S., Miyata T., Ohshima K., Seto M. Array CGH profiling of immunohistochemical subgroups of diffuse large B-cell lymphoma shows distinct genomic alterations. Cancer Science (2014)

Murakami-Tonami Y., Kishida S., Takeuchi I., Katou Y., M. Maris J., Ichikawa H., Kondo Y., Sekido Y., Shirahige K., Murakami H., Kadomatsu K. Inactivation of SMC2 shows a synergistic lethal response in MYCN-amplified neuroblastoma cells. Cell Cycle (2014)

Matsuoka F., Takeuchi I., Agata H., Kagami H., Shiono H., Kiyota Y., Honda H., Kato R. Characterization of time-course morphological features for efficient prediction of osteogenic potential in human mesenchymal stem cells. Biotechnology and Bioengineering (2014)

Chang J., Oikawa S., Iwahashi H., Kitagawa E., Takeuchi I., Yuda M., Kato C., Yamada Y., Ichihara G., Kato M., Ichihara S. Expression of proteins associated with adipocyte lipolysis was significantly changed in the adipose tissues of the obese spontaneously hypertensive/NDmcr-cp rat. Diabetology and Metabolic Syndrome (2014)

[Conference Papers]

Suzumura S., Ogawa K., Sugiyama M., Takeuchi I. Outlier Path: A Homotopy Algorithm for Robust SVM. Proceedings of International Conference on Machine Learning (ICML) (2014)

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2013

[Journal Papers]

duVerle D., Takeuchi I., Murakami-Tonami Y., Kadomatsu K., Tsuda K. Discovering Combinatorial Interactions in Survival Data. Bioinformatics (2013)

Sugiyama M., Kanamori T., Suzuki T., du Plessis MC., Liu S., Takeuchi I. Density-Difference Estimation. Neural Computation (2013)

Natsume A., Ito M., Katsushima K., Ohka F., Hatanaka A., Shinjo K., Sato S., Takahashi S., Ishikawa Y., Takeuchi I., Shimogawa H., Uesugi M., Okano H., Kim S., Wakabayashi T., Jean-Pierre I., Sekido Y., Kondo Y. Chromatin regulator PRC2 is a key regulator of epigenetic plasticity in glioblastoma. Cancer Research (2013)

Matsuoka F., Takeuchi I., Agata H., Kagami H., Shiono H., Kiyota Y., Honda H., Kato R. Morphology-based prediction of osteogenic differentiation potential of human mesenchymal step cells. Plos One (2013)

Yoshioka S., Tsukamoto Y., Hijiya N., Nakada C., Uchida T., Matsuura K., Takeuchi I., Seto M., Kawano K., Moriyama M. Genomic profiling of oral squamous cell carcinoma by array-based comparative genomic hybridization. Plos One (2013)

[Conference Papers]

Takeuchi I., Hongo T., Sugiyama M., Nakajima S. Parametric Task Learning. Proceedings of Neural Information Processing Systems (NIPS) (2013)

Nakajima S., Takeda A., D. Babacan S., Sugiyama M., Takeuchi I. Global solver and its efficient approximation for variational bayesian low-rank subspace clustering. Proceedings of Neural Information Processing Systems (NIPS) (2013)

Ogawa K., Suzuki Y., Takeuchi I. Safe screening of non-support vectors in pathwise SVM computation. Proceedings of International Conference on Machine Learning (ICML) (2013)

Ogawa K., Imamura M., Takeuchi I., Sugiyama M. Infinitesimal annealing for training semi-supervised support vector machines. Proceedings of International Conference on Machine Learning (ICML) (2013)

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2012

[Journal Papers]

Karasuyama M., Harada N., Sugiyama M., Takeuchi I. Multi-parametric Solution-path Algorithm for Instance-weighted Support Vector Machines. Machine Learning (2012)

Chang J., Oikawa S., Ichihara G., Nanpei Y., Hotta Y., Yamada Y., Tada-Oikawa S., Iwahashi H., Kitagawa E., Takeuchi I., Yuda M., Ichihara S. Altered gene and protein expression in liver of the obese spontaneously hypertensive/NDmcr-cp rat. Nutrition and Metabolism (2012)

Shinjo K., Okamoto Y., An B., Yokoyama T., Takeuchi I., Fujii M., Osada H., Usami N., Hasegawa Y., Ito H., Hida T., Fujimoto N., Kishimoto T., Sekido Y., Kondo Y. Integrated analysis of genetic and epigenetic alterations reveals CpG island methylator phenotype associated with distinct clinical characters of lung adenocarcinoma. Carcinogenesis (2012)

Okamoto Y., Ito A., Sawaki S., Nishida T., Takahashi T., Toyota M., Suzuki H., Shinomura Y., Takeuchi I., Shinjo K., Ito K. Yamao B An, H., Fujii M., Murakami H., Osada H., Kataoka H., Joh T., Sekido Y., Kondo Y. Aberrant DNA methylation associated with aggressiveness of gastrointestinal stromal tumor. GUT (2012)

Kishida Y., Natsume A., Kondo Y., Takeuchi I, An B., Okamoto Y., Shinjo K., Saito K., Ando H., Ohka F., Sekido Y., Wakabayashi T. Epigenetic subclassification of meningiomas based on genome-wide DNA methylation analyses. Carcinogenesis (2012)

[Conference Papers]

Sugiyama M., Kanamori T., Suzuki T., Plessis M., Liu S., Takeuchi I. Density-Difference Estimation. Proceedings of Neural Information Processing Systems (NIPS) (2012)

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2011

[Journal Papers]

Matsuura K., Nakada C., Mashio M., Narimatsu T., Yoshimoto T., Tanigawa M., Tsukamoto Y., Hijiya N., Takeuchi I., Nomura T., Sato F., Mimata H., Seto M., Moriyama M. Downregulation of SAV1 plays a role in pathogenesis of high-grade clear cell renal cell carcinoma. BMC Cancer (2011)

Karasuyama M., Takeuchi I. Nonlinear Regularization Path for Quadratic Loss Support Vector Machines. IEEE Transactions on Neural Networks (2011)

Karube K., Nakagawa M., Tsuzuki S., Takeuchi I., Honma K., Nakashima Y., Shimizu N., H. Ko Y., Morishima Y., Ohshima K., Nakamura S., Seto M. Identification of FOXO3 and PRDM1 as tumor suppressor gene candidates in NK cell neoplasms by genomic and functional analyses. Blood (2011)

Kuroda A., Tsukamoto Y., T. Nguyen L., Noguchi T., Takeuchi I., Uchida M., Uchida T., Hijiya N., Nakada C., Okimoto T., Kodama M., Murakami K., Matsuura K., Seto M., Ito H., Fujioka T., Moriyama M. Genomic profiling of submucosal-invasive gastric cancer by array-based comparative genomic hybridization. PLoS One (2011)

Huang P., Kishida S., Cao D., Murakami-Tonami Y., Mu P., Nakaguro M., Koide N., Takeuchi I., Onishi A., Kadomatsu K. NeuroD1 Downregulates Slit2 Expression and Promotes Cell Motility and Tumor Formation of Neuroblastoma. Cancer Research (2011)

Ju H., Okamoto Y., An B., Shinjo K., Kanemitsu Y., Komori K., Hirai T., Shimizu Y., Sano T., Sawaki A., Tajika M., Yamao K., Fujii M., Murakami H., Osada H., Ito H., Takeuchi I., Sekido Y., Kondo Y. Distinct Profiles of Epigenetic Evolution between Colorectal Cancers with and without Metastasis. American Journal of Pathology (2011)

[Conference Papers]

Takeuchi I., Sugiyama M. Target neighbor consistent feature weighting for nearest neighbor classification. Proceedings of Neural Information Processing Systems (NIPS) (2011)

Karasuyama M., Harada N., Sugiyama M., Takeuchi I. Multi-parametric solution path algorithm for instance-weighted support vector machine. Proceedings of IEEE International Workshop on Machine Learning for Signal Processing (MLSP) (2011)

Karasuyama M., Takeuchi I. Suboptimal solution path algorithm for support vector machine. Proceedings of International Conference on Machine Learning (ICML) (2011)

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2010

[Journal Papers]

Ishikawa Y., Takeuchi I. Differentially Aberrant Region Detection in Array CGH Data based on Nearest Neighbor Classification Performance. IPSJ Transactions on Bioinformatics (2010)

Karasuyama M., Takeuchi I. Multiple Incremental Decremental Learning of Support Vector Machines. IEEE Transactions on Neural Networks (2010)

Uchida M., Tsukamoto Y., Uchida T., Ishikawa Y., Nagai T., Hijiya N., Tung N., Nakada C., Kuroda A., Okimoto T., Kodama M., Murakami K., Noguchi T., Matsuura K., Tanigawa M., Seto M., Ito H., Fujioka T., Takeuchi I., Moriyama M. Genomic profiling of gastric carcinoma in situ and adenomas by array-based comparative genomic hybridization. Journal of Pathology (2010)

Ishikawa Y., Takeuchi I., Nakano R. Multi-directional search from the primitive initial point for Gaussian mixture estimation using variational Bayes method. Neural Networks (2010)

Sugiyama M., Takeuchi I., Suzuki T., Kanamori T., Hachiya H., Okanohara D. Least-Squares Conditional Density Estimation. IEICE Transactions on Information and Systems (2010)

[Conference Papers]

Karasuyama M., Takeuchi I. Nonlinear regularization path for the support vector machines with the quadratic loss function. Proceedings of International Joint Conference on Neural Networks (IJCNN) (2010)

Ishikawa Y., Takeuchi I. Detecting differentially aberrant genomic regions in multi-sample array CGH experiments using nearest-neighbor multivariate test. Proceedings of International Joint Conference on Neural Networks (IJCNN) (2010)

Sugiyama M., Takeuchi I., Suzuki T., Kanamori T., Hachiya H., Okanohara D. Conditional density estimation via least-squares density ratio estimation. Proceedings of International Conference on Artificial Intelligence and Statistics (AISTATS) (2010)

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2009

[Journal Papers]

Karasuyama M., Takeuchi I., Nakano R. Efficient leave-m-out cross-validation of support vector regression by generalizing decremantal algorithm. New Generation Computing (2009)

Takeuchi I., Nomura K., Kanamori T. Nonparametric conditional density estimation using piecewise-linear solution path of kernel quantile regression. Neural Computation (2009)

Sugiyama M., Kanamori T., Suzuki T., Hido S., Sese J.,Takeuchi I., Wang L. A density-ratio framework for statistical data processing. IPSJ Transactions on Computer Vision and Applications (2009)

Nakagawa M., Oshiro A., Karnan S., Tagawa H., Usunomiya A., Nakamura S., Takeuchi I., Ohshima K., Seto M. Array comparative genomic hybridization analysis of PTCL-U reveals a distinct subgroup with genetic alterations similar to lymphoma-type adult T-cell leukemia/lymphoma. Clinical Cancer Research (2009)

Takeuchi I., Tagawa H., Tsujikawa A., Nakagawa M., Katayama M., Guo Y., Seto M. The potential of copy number gains and losses, detected by array-based comparative genomic hybridization, for computational differential diagnosis of B-cell lymphomas and genetic regions involved in lymphomagenesis. Haematologica-The Hematology Journal (2009)

[Conference Papers]

Ishikawa Y., Takeuchi I., Nakano R. Variational Bayes from the Primitive Initial Point for Gaussian Mixture Estimation. Proceedings of International Conference on Neural Information Processing (ICONIP) (2009)

Harada N., Ishikawa Y., Takeuchi I., Nakano R. A Bayesian Graph Clustering Approach Using Degree Distribution Prior. Proceedings of International Conference on Neural Information Processing (ICONIP) (2009)

Takeuchi I., Nakagawa M., Seto M. Metric Learning for DNA microarray data analysis. Proceedings of Journal of Physics (2009)

Karasuyma M., Takeuchi I. Multiple incremental decremental learning of support vector machine. Proceedings of Neural Information Processing Systems (NIPS) (2009)

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2008

[Journal Papers]

Tsukamoto Y., Karnan T, Uchida, S., Noguchi T., Tung N., Tanigawa M., Takeuchi I., Matsuura K., Hijiya N., Nakada C., Kishida T., Ito H., Murakami K., Fujioka T., Seto M., Moriyama M. Genome-wide analysis of DNA copy number alterations and gene expression in gastric cancer. Journal of Pathology (2008)

[Conference Papers]

Karasuyama M., Takeuchi I., Nakano R. Reducing SVR support vectors by using backward deletion. Proceedings of International Conference on Knowledge Based Electronic Systems (KES) (2008)

Takeuchi I. Statistical significance analysis of gene groups using nearest-neighbor classification performance. Proceedings of Joint International Conference on Soft Computing and Intelligent Systems and International Symposium on advanced Intelligent Systems (SCIS) (2008)

Moriguchi H., Takeuchi I. Adaptive kernel quantile regression for anomaly detection of time series. Proceedings of Joint International Conference on Soft Computing and Intelligent Systems and International Symposium on advanced Intelligent Systems (SCIS) (2008)

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2007 and Before

[Journal Papers]

Yoshimoto T., Matsuura K., Karnan S., Tagawa H., Nakada C., Tanigawa M., Tsukamoto Y., Uchida T., Kashima K., Akizuki S., Takeuchi I., Sato F., Mimata H., Seto M., Moriyama M. High-resolution analysis of DNA copy number alterations and gene expression in renal clear cell carcinoma. Journal of Pathology (2007)

Fukuhara N., Nakamura T., Nakagawa M., Tagawa H., Takeuchi I., Yatabe Y., Morishima Y., Nakamura S., Seto M. Chromosomal Imbalances are associated with outcome of helicobacter pylori eradication in t(11;18) (q21;q21) negative gastric mucosa-associated lymphoid tissue lymphomas. Genes, Chromosomes and Cancer (2007)

Takeuchi I., Le QV., Sears TD., Smola AJ. Nonparametric quantile estimation. Journal of Machine Learning Research (2006)

Kanamori T., Takeuchi I. Conditional mean estimation under asymmetric and heteroscedastic error by linear combination of quantile regressions. Computational Statistics and Data Analysis (2006)

Takeuchi I., Bengio Y., Kanamori T. Robust regression with asymmetric heavy-tail noise distributions. Neural Computation (2002)

Takeuchi I., Furuhashi T. Modeling for dynamic systems with fuzzy sequential knowledge. Studies in Fuzziness and Soft Computing (2001)

Takeuchi I., Furuhashi T. Modeling of sensory/motor systems for autonomous agents. Journal of Artificial Life and Robotics (2000)

Takeuchi I., Furuhashi T. Acquisition of manipulative grounded symbols for integration of symbolic processing and stimulus-reaction type parallel processing. The International Journal of the Robotics Society of Japan (1997)

[Conference Papers]

Takeuchi I., Nomura K., Kanamori T. The entire solution path of kernel-based nonparametric conditional quantile estimator. Proceedings of International Joint Conference on Neural Networks (IJCNN) (2006)

Takeuchi I., Furuhashi T. Non-crossing quantile regression by SVM. Proceedings of International Joint Conference on Neural Networks (IJCNN) (2004)

Takeuchi I., Yamanaka N., Furuhashi T. Robust regression under asymmetric or/and non-constant variance error by simultaneously training conditional quantiles. Proceedings of International Joint Conference on Neural Networks (IJCNN) (2003)

Bengio Y., Takeuchi I., Kanamori T. The challenge of non-linear regression on large datasets with asymmetric heavy tail. Proceedings of Joint Statistical Meetings (JSM) (2002)

Chapados N., Bengio Y., Vincent P., Dugas C., Ghosn, C., Takeuchi I., Meng L. Estimating car insurance premia: a case study in high-dimensional data inference. Proceedings of Neural Information Processing Systems (NIPS) (2000)

Takeuchi I., Furuhashi T. A study on fuzzy modeling for dynamic characteristic. Proceedings of IEEE International Conference on Systems, Man and Cybernetics (IEEE-SMC) (1999)

Takeuchi I., Furuhashi T. A proposal of fuzzy modeling for dynamic characteristics in state-space description. Proceedings of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1999)

Takeuchi I., Furuhashi T. Integration of symbolic processing and parallel distributed processing by acquisition of manipulative grounded symbol. Proceedings of World Automation Congress (WAC) (1998)

Takeuchi I., Furuhashi T. Self-organization of grounded symbols for fusions of symbolic processing and parallel distribted processing. Proceedings of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (1998)

Takeuchi I., Furuhashi T. A proposal of architecture for intelligent systems with manipulative grounded symbol. Proceedings of The 2nd International Conference on Knowledge Based Electronic Systems (KES) (1998)

Takeuchi I., Furuhashi T. A proposal of self-organizing network for acquisition of vague concept. Proceedings of Asian Fuzzy System Symposium (AFSS) (1996)

Takeuchi I., Furuhashi T. A self-organizing network for acquisition of vague concept. Proceedings of Asia-Pacific Conference on Simulated Evolution and Learning (SEAL) (1996)