Google Scholar Citation

My google scolor citation

Preprint

My arXiv paper list

2021 or After

  • Diptesh Das, Vo Nguyen Le Duy, Hiroyuki Hanada, Koji Tsuda, Ichiro Takeuchi. ''Fast and More Powerful Selective Inference for Sparse High-order Interaction Model''. Proceedings of AAAI Conference on Artificial Intelligence (AAAI2022) Feb. 2022
  • Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi. ''Bayesian Quadrature Optimization for Probability Threshold Robustness Measure''. Neural Computation (to appear)
  • Tomoki Yoshida, Ichiro Takeuchi, Masayuki Karasuyama. ''Distance Metric Learning for Graph Structured Data''. Machine Learning (to appear)
  • Rory Bunker, Keisuke Fujii, Hiroyuki Hanada, Ichiro Takeuchi. Supervised Sequential Pattern Mining of Event Sequences in Sport to Identify Important Patterns of Play: An Application to Rugby Union. PLOS ONE, vol.6, no.9, e0256329 (2021)
  • Kazuya Sugiyama, Vo Nguyen Le Duy, Ichiro Takeuchi. More Powerful and General Selective Inference for Stepwise Feature Selection using Homotopy Method. Proceedings of International Conference on Machine Learning 2021 (ICML2021) Jul. 2021
  • Yu Inatsu, Shogo Iwazaki, Ichiro Takeuchi. Active Learning for Distributionally Robust Level-Set Estimation. Proceedings of International Conference on Machine Learning 2021 (ICML2021) Jul. 2021
  • Duy N.L.V., 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:
  • Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi. Mean-Variance Analysis in Bayesian Optimization under Uncertainty. The 24th International Conference on Artifical Intelligence and Statistics (AISTATS2021). APR 2021
  • Vo Nguyen Le Duy, Ichiro Takeuchi. Parametric Programming Approach for More Powerful and General Lasso Selective Inference. The 24th International Conference on Artifical Intelligence and Statistics (AISTATS2021). APR 2021
  • Ryoichi Koga, Noriaki Hashimoto, Tatsuya Yokota, Masato Nakaguro, Kei Kohno, Sigeo Nakamura, Ichiro Takeuchi and Hidekata Hontani. Detection of DLBCL regions in H&E stained whole slide pathology images using Bayesian U-Net Proceedings Volume 11792, International Forum on Medical Imaging in Asia 2021; 1179203 (2021)
  • Ryoichi Koga, Noriaki Hashimoto, Tatsuya Yokota, Masato Nakaguro, Kei Kohno, Sigeo Nakamura, Ichiro Takeuchi and Hidekata Hontani. 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; 117920R (2021)
  • Yang, Zijian, Suzuki Shinya, Tanibata Naoto, Takeda Hayami, Nakayama Masanobu, Karasuyama Masayuki, Takeuchi Ichiro. 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, 125, 152–160 (2021). mm yyyy
  • Koki Ueno, Kazuhide Ichikawa, Kosei Sato, Daisuke Sugita, Satoshi Yotsuhashi, Ichiro Takeuchi. Robust and efficient calculation of activation energy by automated path search and density functional theory. Physical Review Materials: vol. 5, 033801 (2021)
  • Keiichi Inoue, Masayuki Karasuyama, Ryoko Nakamura, Masae Konno, Daichi Yamada, Kentaro Mannen, Takashi Nagata, Yu Inatsu, Hiromu Yawo, Kei Yura, Oded Béjà, Hideki Kandori, Ichiro Takeuchi. Exploration of natural red-shifted rhodopsins using a machine learning-based Bayesian experimental design. Communication Biology 4, Article number: 362 (2021)
  • Shinya Suzumura, Kazuya Nakagawa, Yuta Umezu, Koji Tsuda, Ichiro Takeuchi. Selective inference for high-order interaction features selected in a stepwise manner. IPSJ Transactions on Bioinformatics: vol.14, pp.1-11 (2021)

    2020

  • 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. vol.25, 101538. Dec 2020
  • Shogo Iwazaki, Yu Inatsu, Ichiro Takeuchi. Bayesian Experimental Design for Finding Reliable Level Set under Input Uncertainty IEEE Access. vol.8, pp.203982-203993 Nov 2020
  • Vo Nguyen Le Duy, Hiroki Toda, Ryota Sugiyama, Ichiro Takeuchi. Computing Valid p-value for Optimal Changepoint by Selective Inference using Dynamic Programming. Proceedings of 34th Conference on Neural Information Processing Systems (NeurIPS2020). Dec 2020
  • Inatsu Y., Karasuyama M., Inoue K., Takeuchi I. Active learning for level set estimation under input uncertainty and its extensions. Neural Computation: vol.32, pp.2486-2531. Dec 2020
  • Maho Harada, Hayami Takeda, Shinya Suzuki, Koki Nakano, Naoto Tanibata, Masanobu Nakayama, Masayuki Karasuyama, Ichiro Takeuchi. Bayesian-optimization-guided Experimental Search of NASICON-type Solid Electrolytes for All-solid-state Li-ion Batteries. Journal of Materials Chemistry A: vol.2020-8, pp.15103-15109. Jul 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 (ICML2020). Jul 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: vol.32, pp.1998-2031 OCT 2020
  • Yu Inatsu, Daisuke Sugita, Kazuaki Toyoura, Ichiro Takeuchi. Active Learning for Enumerating Local Minima Based on Gaussian Process Derivatives. Neural Computation: vol.32, pp.2032-2068. OCT 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: vol.15-6: e0233782. JUN 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: vol.101, pp.184117. MAY 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: vol.8, 041112. Published Online: APR 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 2020 (CVPR2020), 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 2020 (CVPR2020), 2020.

    2019

  • Ndiaye E., Takeuchi I. Computing Full Conformal Prediction Set with Approximate Homotopy Proceedings of 33rd Conference on Neural Information Processing Systems (NeurIPS2019). Dec 2019.
  • Yoshida T., Takeuchi I., Karasuyama M. Safe Triplet Screening for Distance Metric Learning. Neural Computation: vol.31, pp.432-2491, Dec 2019. DOI: 10.1162/neco_a_01240
  • 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). Oct 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: vol.130, paper no.104907. Sep 2019. DOI: 10.1016/j.envint.2019.104907
  • 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 (KDD2019). Aug 2019. DOI: 10.1145/3292500.3330845 DOI: P-GS: 90 -->
  • Umezu Y., Takeuchi I. Selective Inference via Marginal Screening for High Dimensional Classification. Japanese Journal of Statistics and Data Science: vol.2, pp.559-589. Aug 2019. DOI: 10.1007/s42081-019-00058-8
  • Ndiaye Y., Le T., Fercoq O., Salmon J., Takeuchi I. Safe Grid Search with Optimal Complexity. Proceedings of International Conference on Machine Learning (ICML2019). Jun 2019
  • Yamada, M., Wu, D., Tsai Y-H-H., Hirofumi Ota, Salakhutdinov, R., Takeuchi, I., Fukumizu, K. Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator. Proceedings of International Conference on Learning Representation (ICLR 2019). May 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 (Percom2019 Workshops). Mar 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: vol.33, pp.134-152. Feb 2019. DOI: 10.1080/01691864.2019.1571438
  • 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: vol.111, pp.34-42. Jan 2019. DOI: 10.1016/j.ygeno.2017.12.010

    2018

  • 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: vol.18, pp.1–9. Nov 2018. DOI: 10.1002/tcr.201800129
  • 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: vol.2, paper no.113802. Nov 2018. DOI: 10.1103/PhysRevMaterials.2.113802
  • 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: vol.8, paper no.15580. Oct 2018. DOI: 10.1038/s41598-018-33984-w
  • 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: vol.9, paper no.e02447. Oct 2018 DOI: 10.1002/ecs2.2447
  • 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 (KDD2018). Aug 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) 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: vol.41, pp.2724-2732. May 2018. DOI: 10.3892/ijmm.2018.3453
  • 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: vol.8, paper no.5845. Apr 2018 DOI: 10.1038/s41598-018-23852-y
  • Yamada M., Umezu Y., Fukumizu K., Takeuchi I. Post Selection Inference with Kernels. Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS2018) Apr 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: vol.97, paper no.125124. Mar 2018. DOI:10.1103/PhysRevB.97.125124
  • 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 (AAAI2018) Feb 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: vol.2, pp.66-77 Jan 2018. DOI: 10.1093/neuonc/nox132.

    2017

  • 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: vol.49, paper no.e409. Dec 2017. DOI: 10.1038/emm.2017.209
  • 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: vol.16, pp.5823-5832. Nov 2017. DOI: 10.3892/mmr.2017.7334
  • 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: vol.25(7), paper no.075003. Aug 2017 DOI: 10.1088/1361-651X/aa8276
  • 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 (ICML2017). Aug 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: vol.8, pp.80492-80505. Jul 2017. DOI: 10.18632/oncotarget.19287
  • 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: vol.8, pp.43068-43079 Jun 2017. DOI: 10.18632/oncotarget.17474.
  • 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: vol.8, pp.38950-38961. Jun 2017. DOI: 10.18632/oncotarget.17159.
  • 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: vol.8, pp.33527-33535 May 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: vol.39, pp.1091-1100. May 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-CCS2017). Apr 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: vol.293, paper no.371-379. Apr 2017 DOI: 10.1007/s00438-017-1394-1
  • 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: vol.93, paper no.054112. Feb 2017. DOR: 10.1103/PhysRevB.93.054112
  • Suzumura S., Ogawa K., Karasuyama M., Sugiyama M., Takeuchi I. Homotopy continuation approaches for robust SV classification and regression. Machine Learning: vol.106(7), pp.1009–1038. Feb 2017 DOI: 10.1007/s10994-017-5627-7
  • 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 8, 45259-45273 (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 39, 1477-1491 (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 8, 39296-39308 (2017)

    2016

  • Takada T., Hanada H., Yamada Y., Sakuma J., Takeuchi I. Secure Approximation Guarantee for Cryptographically Private Empirical Risk Minimization. Proceedings of {\bf Asian Conference on Machine Learning (ACML2016). Nov 2016.
  • 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: vol.11(3), pp.299-314. Sep 2016. DOI: 10.1016/j.orcp.2016.08.008
  • Nakagawa K., Suzumura S., Karasuyama M., Tsuda K., Takeuchi I. Safe Pattern Pruning: An Efficient Approach for Predictive Pattern Mining. Proceedings of {\bf ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2016). Aug 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: vol.6, paper no.31615. Aug 2016. DOI: 10.1038/srep31615
  • Shibagaki A., Karasuyama M., Hatano K., Takeuchi I. Simultaneous safe screening of features and samples in doubly sparse modeling. Proceedings of {\bf International Conference on Machine Learning (ICML2016). Jun 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: vol.76(9), pp.2612-2625. May 2016. DOI:10.1158/0008-5472
  • 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: vol.30, pp.1568–1579. Mar 2016. DOI: 10.1038/leu.2016.67

    2015

  • Shibagaki A., Suzuki Y., Karasuyama M., Takeuchi I. Regularization Path of Cross-Validation Error Lower Bounds. Proceedings of Neural Information Processing Systems (NIPS2015) Dec 2015.
  • 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: vol.35, pp.1290-1300. Oct 2015. DOI: 10.1002/cam4.351.
  • 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 (KDD2015) Aug 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: vol.3, pp.413-419. May 2015. DOI: 10.3892/br.2015.440
  • 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: vol.3, pp.347-354. May 2015. DOI: 10.3892/br.2015.439
  • 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: vol.35, pp.1189-1198. Mar 2015. DIO: 10.3892/ijmm.2015.2151
  • 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: vol.4(1), paper no.112-124. Jan 2015. DOI:doi: 10.1002/cam4.351

    2014

  • 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: vol.2014, paper no.860241 Aug 2014. DOI: http://dx.doi.org/10.1155/2014/860241
  • 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: vol.105, pp.897-904. Jul 2014. DOI: 10.1111/cas.12442
  • Suzumura S., Ogawa K., Sugiyama M., Takeuchi I. Outlier Path: A Homotopy Algorithm for Robust SVM. Proceedings of International Conference on Machine Learning (ICML2014). Jun 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: vol.9, paper no.e93952. Apr 2014. DOI: 10.1371/journal.pone.0093952
  • Isu N., Hasegawa T., Takeuchi I., Morimoto A. Quantitative analysis of time-course development of motion sickness by in-vehicle video watching. Displays: vol.35, pp.90-97. Apr 2014. DOI: 10.1016/j.displa.2014.01.003
  • 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: vol.105. pp.481-489. Apr 2014. DOI: 10.1111/cas.12378
  • 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: vol.13, pp.1-17. Apr 2014. DOI: 10.4161/cc.27983
  • 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: vol.111, pp.1430-1439 Jan 2014. DOI: 10.1002/bit.25189
  • 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: vol.6, pp.1-9. Jan 2014. DOI: 10.1186/1758-5996-6-8

    2013

  • Takeuchi I., Hongo T., Sugiyama M., Nakajima S. Parametric Task Learning. Proceedings of Neural Information Processing Systems (NIPS2013). Dec 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 (NIPS2013). Dec 2013.
  • duVerle D., Takeuchi I., Murakami-Tonami Y., Kadomatsu K., Tsuda K. Discovering Combinatorial Interactions in Survival Data. Bioinformatics: vol.29, pp.3053-3059. Dec 2013. DOI: 10.1093/bioinformatics/btt532
  • Sugiyama M., Kanamori T., Suzuki T., du Plessis MC., Liu S., Takeuchi I. Density-Difference Estimation. Neural Computation: vol.25, pp.2734-2775. Oct 2013. DOI: 10.1162/NECO_a_00492
  • 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: vol.73, pp.4559-4570. Jul 2013. DOI: 10.1158/0008-5472.CAN-13-0109
  • Ogawa K., Suzuki Y., Takeuchi I. Safe screening of non-support vectors in pathwise SVM computation. Proceedings of International Conference on Machine Learning (ICML2013). Jun 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 (ICML2013). Jun 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: vol.8, paper no.e55082. Feb 2013. DOI: 10.1371/journal.pone.0055082
  • 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: vol.8, paper no.e56165. Feb 2013. DOI: 10.1371/journal.pone.0056165

    2012

  • Sugiyama M., Kanamori T., Suzuki T., Plessis M., Liu S., Takeuchi I. Density-Difference Estimation. Proceedings of Neural Information Processing Systems (NIPS2012) Dec 2012.
  • Karasuyama M., Harada N., Sugiyama M., Takeuchi I. Multi-parametric Solution-path Algorithm for Instance-weighted Support Vector Machines. Machine Learning: vol.88, pp.297-330. Sep 2012. DOI: 10.1007/s10994-012-5288-5
  • 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: vol.9, paper no.87. Sep 2012. DOI: 10.1186/1743-7075-9-87.
  • 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: vol.33, pp.1277-1285. Jul 2012. DOI: 10.1093/carcin/bgs154
  • 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: vol.61, pp.392-401. Mar 2012. DOI: 10.1136/gut.2011.241034
  • 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: vol.32, pp.436-441. Feb 2012. DOI: 10.1093/carcin/bgr260.

    2011

  • Takeuchi I., Sugiyama M. Target neighbor consistent feature weighting for nearest neighbor classification. Proceedings of Neural Information Processing Systems (NIPS2011) Dec 2011.
  • 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: vol.11, paper no.523. Dec 2011. DOI: 10.1186/1471-2407-11-523
  • Karasuyama M., Takeuchi I. Nonlinear Regularization Path for Quadratic Loss Support Vector Machines. IEEE Transactions on Neural Networks: vol.22, pp.1613-1625. Oct 2011. DOI: 10.1109/TNN.2011.2164265
  • 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 (MLSP2011) Sep 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: vol.118, pp.3195-3204. Sep 2011. DOI: 10.1182/blood-2011-04-346890
  • Karasuyama M., Takeuchi I. Suboptimal solution path algorithm for support vector machine. Proceedings of International Conference on Machine Learning (ICML2011) Jul 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: vol 6(7), paper no.e22313. Jul 2011. DOI: 10.1371/journal.pone.0022313
  • 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: vol.71, pp.2938-2948. Apr 2011. DOI: 10.1158/0008-5472.CAN-10-3524
  • 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: vol 178(4), pp.1835--1846. Apr 2011. DOI: 10.1016/j.ajpath.2010.12.045

    2010

  • Ishikawa Y., Takeuchi I. Differentially Aberrant Region Detection in Array CGH Data based on Nearest Neighbor Classification Performance. IPSJ Transactions on Bioinformatics: vol 3, pp.70-81. Dec 2010. DOI: 10.11185/imt.5.1266
  • 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 (IJCNN2010). Jul 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 (IJCNN2010) Jul 2010.
  • Karasuyama M., Takeuchi I. Multiple Incremental Decremental Learning of Support Vector Machines. IEEE Transactions on Neural Networks: vol 21(7), pp.1048-1059. Jul 2010. DOI: 10.1109/TNN.2010.2048039
  • Sugiyama M., Takeuchi I., Suzuki T., Kanamori T., Hachiya H., Okanohara D. Conditional density estimation via least-squares density ratio estimation. Proceedings of the 13th International Conference on Artificial Intelligence and Statistics (AISTATS2010) May 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: vol 221(1), pp.96-105 May 2010. DOI: 10.1002/path.2686
  • Ishikawa Y., Takeuchi I., Nakano R. Multi-directional search from the primitive initial point for Gaussian mixture estimation using variational Bayes method. Neural Networks: vol 23(3), pp.356-364. Apr 2010. DOI: 10.1016/j.neunet.2009.08.003
  • Sugiyama M., Takeuchi I., Suzuki T., Kanamori T., Hachiya H., Okanohara D. Least-Squares Conditional Density Estimation. IEICE Transactions on Information and Systems: vol E93-D(3), pp.583-594. Mar 2010. DOI: 10.1587/transinf.E93.D.583

    2009

  • Ishikawa Y., Takeuchi I., Nakano R. Variational Bayes from the Primitive Initial Point for Gaussian Mixture Estimation. Proceedings of the 16th International Conference on Neural Information Processing (ICONIP09) Dec 2009.
  • Harada N., Ishikawa Y., Takeuchi I., Nakano R. A Bayesian Graph Clustering Approach Using Degree Distribution Prior. Proceedings of the 16th International Conference on Neural Information Processing (ICONIP2009) Dec 2009.
  • Takeuchi I., Nakagawa M., Seto M. Metric Learning for DNA microarray data analysis. Proceedings of Journal of Physics: Conference Series Dec 2009.
  • Karasuyma M., Takeuchi I. Multiple incremental decremental learning of support vector machine. Proceedings of Neural Information Processing Systems (NIPS2009). Dec 2009.
  • Karasuyama M., Takeuchi I., Nakano R. Efficient leave-m-out cross-validation of support vector regression by generalizing decremantal algorithm. New Generation Computing: vol.27, pp.307-318. Aug 2009. DOI: 10.1007/s00354-008-0067-3
  • Takeuchi I., Nomura K., Kanamori T. Nonparametric conditional density estimation using piecewise-linear solution path of kernel quantile regression. Neural Computation: vol.21, pp.533-559. Feb 2009. DOI: 10.1162/neco.2008.10-07-628
  • 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: vol.1, pp.183-208. Jan 2009. DOI: 10.2197/ipsjtcva.1.183
  • 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: vol.15, pp.30-38. Jan 2009. DOI: 10.1158/1078-0432.CCR-08-1808
  • 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: vol.94, pp.61-69. Jan 2009. DOI:10.3324/haematol.12986

    2008

  • 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: vol.216, pp.471-82. Dec 2008. DOI: 10.1002/path.2424.
  • Karasuyama M., Takeuchi I., Nakano R. Reducing SVR support vectors by using backward deletion. Proceedings of the International Conference on Knowledge Based Electronic Systems (KES2008) Sep 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 (SCIS2008) Jan 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 (SCIS2008) Jan 2008.

    Before 2007

  • 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: vol.213, pp.392-401. 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: vol.46, pp.784-790. 2007.
  • 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 2006 (IJCNN2006). 2006.
  • Takeuchi I., Le QV., Sears TD., Smola AJ. Nonparametric quantile estimation. Journal of Machine Learning Research: vol.7, pp.1231-1264 2006.
  • Kanamori T., Takeuchi I. Conditional mean estimation under asymmetric and heteroscedastic error by linear combination of quantile regressions. Computational Statistics and Data Analysis: vol.50, pp.3605-3618 2006.
  • Takeuchi I., Furuhashi T. Non-crossing quantile regression by SVM. Proceedings of International Joint Conference on Neural Networks (IJCNN2004). 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 (IJCNN2003). 2003
  • Takeuchi I., Bengio Y., Kanamori T. Robust regression with asymmetric heavy-tail noise distributions. Neural Computation: vol.14, pp.2469-2496. 2002.
  • Bengio Y., Takeuchi I., Kanamori T. The challenge of non-linear regression on large datasets with asymmetric heavy tail. Proceedings of Joint Statistical Meetings (JSM2002). 2002.
  • Takeuchi I., Furuhashi T. Modeling for dynamic systems with fuzzy sequential knowledge. Studies in Fuzziness and Soft Computing: vol.59, pp.104-120 2001.
  • Takeuchi I., Furuhashi T. Modeling of sensory/motor systems for autonomous agents. Journal of Artificial Life and Robotics: vol.4, pp.84-88. 2000.
  • 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 (NIPS2000). 2000.
  • Takeuchi I., Furuhashi T. A study on fuzzy modeling for dynamic characteristic. Proceedings of IEEE International Conference on Systems, Man and Cybernetics (IEEE-SMC99). 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-IEEE1999). 1999.
  • Takeuchi I., Furuhashi T. Integration of symbolic processing and parallel distributed processing by acquisition of manipulative grounded symbol. Proceedings of World Automation Congress (WAC1998). 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-IEEE1998) 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 (KES1998) 1998.
  • 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: vol.12, pp.271-87. 1997.
  • Takeuchi I., Furuhashi T. A proposal of self-organizing network for acquisition of vague concept. Proceedings of Asian Fuzzy System Symposium (AFSS1996). 1996.
  • Takeuchi I., Furuhashi T. A self-organizing network for acquisition of vague concept. Proceedings of Asia-Pacific Conference on Simulated Evolution and Learning (SEAL1996). 1996.