Publications

Journal Papers

84. Keishi Sando, Tam Le, Hideitsu Hino, ``Tree Structure for the Categorical Wasserstein Weisfeiler-Lehman Graph Kernel'', Transactions on Machine Learning Research, to appear

83. Yuhei Takaya, Hideitsu Hino, Caio A. S. Coelho, ``Information-based probabilistic verification scores and predictability measures: Seasonal prediction examples'', Quarterly Journal of the Royal Meteorological Society, to appear

82. Yasuhiko Igarashi, Naoka Nagamura, Masahiro Sekine, Hirokazu Fukidome, Hideitsu Hino, Masato Okada, ``Sparse Coding-Based Multiframe Superresolution for Efficient Synchrotron Radiation Microspectroscopy'', Discover Nano, Volume 20, article number 102, 2025

81. Kyoichi Iwasaki, Hideitsu Hino, ``Dynamics of the accelerated t-SNE'', Transactions on Machine Learning Research, 11 Jun 2025

80. Hiroshi Tamano, Hideitsu Hino, Daichi Mochihashi, ``Misspecifying Non-Compensatory as Compensatory IRT: Analysis of Estimated Skills and Variance'', Behaviormetrika, 05 July 2025

79. Yusei Ito, Yasuo Takeichi, Hideitsu Hino, Kanta Ono, ``Optimal Spectroscopic Measurement Design: Bayesian Framework for Rational Data Acquisition'', Machine Learning: Science and Technology, Volume 6, Number 2, 2025

78. Keishi Sando, Hideitsu Hino, ``Complex non-backtracking matrix for directed graphs'', Journal of Complex Networks, Volume 13, Issue 4, August 2025

77. Tatsu Kuwatani, Hideitsu Hino, Haruka Nishikawa, Shotaro Akaho, ``Data-driven proactive prediction of pumice drifting patterns using similarity search of the Kuroshio current axis'', npj Natural Hazards, Vol. 2, Article number: 34, 2025

76. Hajime Ono, Kazuhiro Minami, Hideitsu Hino, ``When Should We Use Top Coding in Locally Private Estimation? Theoretical Bounds of Performance'', International Journal of Information Security, Volume 24, article number 28, 2025

75. Shin-itiro Goto, Hideitsu Hino, ``Fast symplectic integrator for Nesterov-type acceleration method'', Japan Journal of Industrial and Applied Mathematics, (source code), Vol. 42, pages 331--372, 2025

74. Shogo Sagawa, Hideitsu Hino, ``Gradual Domain Adaptation via Normalizing Flows'', Neural Computation, vol. 37, issue, pp. 3522–568, 2025

73. Hideitsu Hino, Keisuke Yano, ``An embedding structure of determinantal point process'', Information Geometry, Vol. 7, pages 523--542, 2024 (corrigendum)

72. Takuto Sato, Hideitsu Hino, Hiroyuki Kusaka, ``Separating urban heat island circulation and convective cells through dynamic mode decomposition'', Atmospheric Science Letters, 25 (12), e1279, 2024

71. Yusei Ito, Yasuo Takeichi, Hideitsu Hino, Kanta Ono, ``Rational partitioning of spectral feature space for effective clustering of massive spectral image data'', Scientific Reports, 14, Article number: 22549 (2024)

70. Masanari Kimura, Hideitsu Hino, ``A Short Survey on Importance Weighting for Machine Learning'', Transactions on Machine Learning Research, Published: 14 May 2024

69. Kenta Ueki, Hideitsu Hino, Tatsu Kuwatani, ``An introduction to SGTPPR: Sparse Geochemical Tectono-magmatic setting Probabilistic membershiP discriminatoR'', Geochemistry, Geophysics, Geosystems (G-cubed), vol. 25, 2024

68. Takahiro Kawashima, Hideitsu Hino, ``Minorization-Maximization for Learning Determinantal Point Processes'', Transactions on Machine Learning Research, 2023

67. Jun Narita, Takao Murakami, Hideitsu Hino, Masakatsu Nishigaki, Tetsushi Ohki, ``Synthesizing Differentially Private Location Traces Including Co-Locations'', International Journal of Information Security, 29-th August, 2023

66. Kotaro Sakamoto, Hideaki Ishibashi, Rei Sato, Shinichi Shirakawa, Youhei Akimoto, Hideitsu Hino, ``ATNAS: Automatic Termination for Neural Architecture Search'', Neural Networks, code available from here, Volume 166, September 2023, Pages 446-458

65. Yuhei Takaya, Kensuke K. Komatsu, Hideitsu Hino, Frédéric Vitart, ``Information-based Probabilistic Verification Scores for Two-dimensional Ensemble Forecast Data: A Madden-Julian Oscillation Index Example'', Monthly Weather Review, Vol.151, issue 9, pp. 2245–2255, 2023

64. Atsushi Nakao, Tatsu Kuwatani, Kenta Ueki, Kenta Yoshida, Taku Yutani, Hideitsu Hino, Shotaro Akaho, ``Regression analysis and variable selection to determine the key subduction-zone parameters that determine the maximum earthquake magnitude'', Earth, Planets and Space, vol. 75, Article number: 78 (2023)

63. Shogo Sagawa, Hideitsu Hino, ``Cost-effective Framework for Gradual Domain Adaptation with Multifidelity'', Neural Networks, Volume 164, July 2023, Pages 731-741

62. Hideitsu Hino, Shinto Eguchi, ``Active Learning by Query by Committee with Robust Divergences'', Information Geometry, Vol. 6, pages 81–106 (2023)

61. Hideitsu Hino, Shotaro Akaho, Noboru Murata, ``Geometry of EM and related iterative algorithms'', Information Geometry, Volume 7, pages 39–77, (2024)

60. Hiroshi Sekiguchi, Noboru Ohta, Hideaki Ishibashi, Hideitsu Hino, Masaichiro Mizumaki, ``End-condition for solution small angle X-ray scattering measurements by kernel density estimation", Science and Technology of Advanced Materials: Methods, Volume 2 Issue 1, pages 426-434 (2022)

59. Atsushi Nakao, Tatsu Kuwatani, Kenta Ueki, Kenta Yoshida, Taku Yutani, Hideitsu Hino, Shotaro Akaho, ``Subduction-zone parameters that control slab behavior at the 660-km discontinuity revealed by logistic regression analysis and model selection'', Frontiers in Earth Science, section Geochemistry, 26 October 2022

58. Tatsu Kuwatani, Hideitsu Hino, Kenji Nagata, Takahiro Kawashima, Mitsuhiro Toriumi, Masato Okada, ``Hyperparameter estimation using resolution matrix for Bayesian sensing'', Inverse Problems, Vol. 38 (12), 2022

57. Kenta Ueki, Hideitsu Hino, Tatsu Kuwatani, ``Extracting the geochemical characteristics of magmas in different global tectono-magmatic settings using sparse modeling'', Frontiers in Earth Science, section Geochemistry, 07 October 2022

56. Takahiro Kawashima, Hideitsu Hino, ``Gaussian Process Koopman Mode Decomposition'', Neural Computation, vol. 35 (1), pp.82--103, 2022

55. Toshimitsu Aritake, Hideitsu Hino, ``Unsupervised Domain Adaptation for Extra Features in the Target Domain Using Optimal Transport'', Neural Computation, vol. 34 (12), pp.2432--2466, 2022

54. Masanari Kimura, Hideitsu Hino, ``Information Geometrically Generalized Covariate Shift Adaptation'', Neural Computation, 34 (9): 1944–1977, 2022

53. Mizuo Nagayama, Toshimitsu Aritake, Hideitsu Hino, Takeshi Kanda, Takehiro Miyazaki, Masashi Yanagisawa, Shotaro Akaho, Noboru Murata, ``Detecting cell assemblies by NMF-based clustering from calcium imaging data'', Neural Networks, Volume 149, May 2022, Pages 29-39

52. Hideaki Miyamoto, Takafumi Niihara, Koji Wada, Kazunori Ogawa, Hiroki Senshu, Patrick Michel, Hiroshi Kikuchi, Ryodo Hemmi, Tomoki Nakamura, Akiko M. Nakamura, Naoyuki Hirata, Sho Sasaki, Erik Asphaug, Daniel T. Britt, Paul A. Abell, Ronald-Louis Ballouz, Oliver S. Banouin, Nicola Baresi, Maria A. Barucci, Jens Biele, Matthias Grott, Hideitsu Hino, Peng K. Hong, Takane Imada, Shingo Kameda, Makito Kobayashi, Guy Libourel, Katsuro Mogi, Naomi Murdoch, Yuki Nishio, Shogo Okamoto, Yuichiro Ota, Masatsugu Otsuki, Katharina A. Otto, Naoya Sakatani, Yuta Shimizu, Tomohiro Takemura, Naoki Terada, Masafumi Tsukamoto, Tomohiro Usui, Konrad Willner, ``Surface Environment of Phobos and Phobos Simulant UTPS'', Earth, Planets and Space, vol. 73, Article number: 214, 2021

51. Takuya Takabatake, Makoto Yamamoto, Hideitsu Hino, ''Algorithm for Searching Optimal Set Values of Absorption Chiller System Using Bayesian Optimization'', Science and Technology for the Built Environment, Volume 28 (2), Pages 188-199, 2022

50. Tetsuro Ueno, Hideaki Ishibashi, Hideitsu Hino, Kanta Ono, "Automated stopping criterion for spectral measurements with active learning", npj Computational Materials, 7, Article number: 139, 2021. (code available from here)

49. Masanari Kimura, Hideitsu Hino, "α-Geodesical Skew Divergence", Entropy, 23(5), 528, 2021

48. Toshimitsu Aritake, Hideitsu Hino, Shigeyuki Namiki, Daisuke Asanuma, Kenzo Hirose, Noboru Murata, ``Fast and robust multiplane single molecule localization microscopy using deep neural network", Neurocomputing, Vol. 451 (3) pp. 279-289, 2021

47. Yusuke Taguchi, Hideitsu Hino, Keisuke Kameyama, "Pre-training Acquisition Functions by Deep Reinforcement Learning for Fixed Budget Active Learning'', Neural Processing Letters, vol. 53(3), pp. 1945-1962, 2021 (code available from here)

46. Hideitsu Hino, "Active Learning: Problem Settings and Recent Developments", Journal of Japan Statistical Society (in Japanese: 能動学習：問題設定と最近の話題), 50 (2), 317-342, 2021

45. Yuta Suzuki, Hideitsu Hino, Takafumi Hawai, Kotaro Saito, Masato Kotsugi, Kanta Ono, "Symmetry prediction and knowledge discovery from X-ray diffraction patterns using an interpretable machine learning approach", Scientific Reports, 10, Article number: 21790,11pages, 2020

44. Toshimitsu Aritake, Hideitsu Hino, Shigeyuki Namiki, Daisuke Asanuma, Kenzo Hirose, Noboru Murata, "Single-Molecule Localization by Voxel-Wise Regression Using Convolutional Neural Network”, Results in Optics, Volume 1, 11pages, November 2020

43. Shin-itiro Goto, Hideitsu Hino, "Diffusion equations from master equations - A discrete geometric approach -", Journal of Mathematical Physics, 61, 113301-27 (27 pages), 2020

42. Keishi Sando, Hideitsu Hino, "Modal Principal Component Analysis", Neural Computation, (code available from here), Vol. 32, No. 10, pp.1901--1935, 2020

41. Takuto Sato, Hiroyuki Kusaka, Hideitsu Hino, "Quantitative Assessment of the Contribution of Meteorological Variables to the Prediction of the Number of Heat Stroke Patients for Tokyo", Scientific Online Letters on the Atmosphere (SOLA), vol. 16, pages 104--108, 2020

40. Takehiro Miyazaki, Takeshi Kanda, Natsuko Tsujino, Ryo Ishii, Daiki Nakatsuka, Mariko Kizuka, Yasuhiro Kasagi, Hideitsu Hino, Masashi Yanagisawa, "Dynamics of cortical local connectivity during sleep/wake states and the homeostatic process", Cerebral Cortex, Volume 30, Issue 7, July 2020, Pages 3977–3990

39. Yu Nishihara, Shunta Doi, Hideitsu Hino, Yuji Higo, and Yoshinori Tange, "Pressure effect on the electromotive force of the type R thermocouple", High Pressure Research, vol. 40, number 2, Pages 205-218, 2020, doi:10.1080/08957959.2019.1705296

38. Shin-itiro Goto, Hideitsu Hino, "Information and contact geometric description of expectation variables exactly derived from master equations", Physica Scripta, vol 95 (1), 20 December 2019

37. Keishi Sando, Shotaro Akaho, Noboru Murata, Hideitsu Hino, "Information Geometry of Modal Linear Regression", Information Geometry, Volume 2, Issue 1, pp. 43–75, 2019

36. Yuta Suzuki, Hideitsu Hino, Masato Kotsugi, Kanta Ono, "Automated estimation of materials parameter from X-ray absorption and electron energy-loss spectra with similarity measures", npj Computational Materials, vol. 5, Article Number: 39, 2019

35. Kotaro Saito, Masao Yano, Hideitsu Hino, Tetsuya Shoji, Akinori Asahara, Hidekazu Morita, Chiharu Mitsumata, Joachim Kohlbrecher, Kanta Ono,"Accelerating small-angle scattering experiments on anisotropic samples using kernel density estimation", Scientific Reports, 9, Article number: 1526 (2019)

34. Sho Sonoda, Keita Nakamura, Yuki Kaneda, Hideitsu Hino, Shotaro Akaho, Noboru Murata, Eri Miyauchi, Masahiro Kawasaki, “EEG Dipole Source Localization with Information Criteria for Multiple Particle Filters”, Neural Networks, vol. 108, pp. 68--82, 2018

33. Taishi Iwasaki, Hideitsu Hino, Masami Tatsuno, Shotaro Akaho, Noboru Murata, “Estimation of neural connections from partially observed neural spikes”, Neural Networks, vol. 108, pp. 172--191, 2018

32. Daigo Shoji, Rina Noguchi, Sihizuka Otsuki, Hideitsu Hino,“Classification of volcanic ash particles using a convolutional neural network and probability”, Scientific Reports, volume 8, Article number: 8111, 2018

31. Kenta Ueki, Hideitsu Hino, and Tatsu Kuwatani, “Geochemical discrimination and characteristics of magmatic tectonic settings; a machine learning-based approach”, Geochemistry, Geophysics, Geosystems (G- cubed), vol. 19, pp. 1327-1347, 2018

30. Takao Murakami, Hideitsu Hino, and Jun Sakuma, “Toward Distribution Estimation under Local Differential Privacy with Small Samples”, Proceedings on Privacy Enhancing Technologies (PoPETs), issue 3, pp.84– 104, 2018

29. Tetsuro Ueno, Hideitsu Hino, Ai Hashimoto, Yasuo Takeichi, Masahiro Sawada, and Kanta Ono, “Adaptive design of an X-ray magnetic circular dichroism spectroscopy experiment with Gaussian process modeling”, npj Computational Materials, vol. 4, Article number: 4 2018

28. Hideitsu Hino, “ider: Intrinsic Dimension Estimation with R”, The R Journal, 9:2, pages 329-341, 2017

27. Ryoko Nakata, Hideitsu Hino, Tatsu Kuwatani, Shoichi Yoshioka, Masato Okada, Takane Hori, “Discontinuous boundaries of slow slip events beneath the Bungo Channel, southwest Japan”, Scientific Reports, Vol. 7, Article number: 6129, 2017

26. Hideitsu Hino, Jun Fujiki, Shotaro Akaho, Noboru Murata, “Local Intrinsic Dimension Estimation by Generalized Linear Modeling,” Neural Computation, Vol. 29, No. 7, pp. 1838–1878, 2017

25. Toshiyuki Kato, Hideitsu Hino, Noboru Murata, “Double sparsity for multi-frame super resolution,” Neurocomputing, Volume 240, 31, pp. 115–126, 2017, code available from here

24. Tomoaki Chiba, Hideitsu Hino, Shotaro Akaho, Noboru Murata, “Time-Varying Transition Probability Matrix Estimation and its Application to Brand Share Analysis”, PLOS ONE, January 11, 2017

23. Takao Murakami, Atsunori Kanemura, Hideitsu Hino, “Group Sparsity Tensor Factorization for Re-identification of Open Mobility Traces”, IEEE Transactions on Information Forensic and Security, Volume: 12, Issue: 3, March 2017, pages 689–704

22. Ken Takano, Hideitsu Hino, Shotaro Akaho, Noboru Murata, “Non-parametric e-mixture estimation”, Neural Computation, Vol. 28, No. 12, Pages 2687–2725, 2016

21. Chendra Hadi Suryanto, Kazuhiro Fukui, Hideitsu Hino, “Protein Fold Classification using Large Margin Combination of Distance Metrics”, IEICE Transactions on Information and Systems, Vol. E99-D, No. 3, pp.-,Mar 2016

20. Hideitsu Hino, Ken Takano, Noboru Murata, “mmpp: a Package for Calculating Similarity and Distance Metrics for Simple and Marked Temporal Point Process”, The R Journal, Vol. 7, Issue 2, pp. 237–248, December 2015

19. Hideitsu Hino, Jun Fujiki, “Adherently Penalized Linear Discriminant Analysis”, Journal of the Japanese Society of Computational Statistics, Vol. 28, pp. 125–137, December 2015

18. Kensuke Koshijima, Hideitsu Hino, and Noboru Murata, “Change-Point Detection in a Sequence of Bags-of-Data”, IEEE Transactions on Knowledge and Data Engineering, Vol. 27, Issue 10, pp. 2632–2644, 2015

17. Hideitsu Hino, Kensuke Koshijima, and Noboru Murata, “Non-Parametric Entropy Estimators Based on Simple Linear Regression”, Computational Statistics & Data Analysis, Vol. 89, pp. 72–84, September 2015

16. Toshiyuki Kato, Hideitsu Hino, and Noboru Murata, “Multi-Frame Image Super Resolution Based on Sparse Coding”, Neural Networks, Vol. 66, pp. 64–78, June 2015, code available from here

15. Hideitsu Hino, “Entropy Power Inequality for Learning Optimal Combination of Kernel Functions”, Journal of Signal Processing Systems, vol. 79, issue 2 , pp 201-210 , May 2015

14. Hideitsu Hino, Noboru Murata, “A Non-parametric Clustering Algorithm With A Quantile-based Likelihood Estimator”, Neural Computation, vol. 26, issue 9, September, pp. 2074-2101, 2014, code available from

13. Alexandre Brouste, Masaaki Fukasawa, Hideitsu Hino, Hiroki Masuda, Masayuki Uchida, Stefano M. Iacus, Ryosuke Nomura, Nakahiro Yoshida, Kengo Kamatani, Teppei Ogihara, Yuta Koike, Yasutaka Shimuzu, “The YUIMA Project: a Computational Framework for Simulation and Inference of Stochastic Differential Equations”, Journal of Statistical Software, vol. 57, issue 4, 2014

12. Atsushi Noda, Hideitsu Hino, Masami Tatsuno, Shotaro Akaho, Noboru Murata, “Intrinsic Graph Structure Estimation Using Graph Laplacian”, Neural Computation, vol. 26, issue 7, Jul, pp. 1455-1483, 2014

11. Hideitsu Hino, Noboru Murata, “Information Estimators for Weighted Observations”, Neural Networks, vol. 46, pp. 260–275, 2013

10. Hideitsu Hino, Keigo Wakayama, Noboru Murata, “Entropy-Based Sliced Inverse Regression”, Computational Statistics and Data Analysis, vol. 67, pp. 105–114, 2013

9. Hideitsu Hino, Haoyang Shen, Noboru Murata, Shinji Wakao, Yasuhiro Hayashi, “A Versatile Clustering Method for Electricity Consumption Pattern Analysis in Households”, IEEE Transactions on Smart Grid, vol. 4, issue 2, pp. 1048–1057, 2013

8. Toshimitsu Aritake, Hideitsu Hino, Noboru Murata, “Learning Ancestral Atom via Sparse Coding”, IEEE Journal of Selected Topics in Signal Processing, vol. 7, issue 4, pp. 586–594, 2013

7. Hideitsu Hino, Nima Reyhani, Noboru Murata, “Multiple Kernel Learning with Gaussianity Measures”, Neural Computation, vol. 24, issue 7, pp.1853–1881, 2012

6. Sho Sonoda, Noboru Murata, Hideitsu Hino, Hiroshi Kitada, Manabu Kano, “A Statistical Model for Predicting the Liquid Steel Temperature in Ladle and Tundish by Bootstrap Filter”, ISIJ International, vol.52, no.6, pp.1096–1101, 2012

5. Shigeru Furuichi, Hideitsu Hino, “Mathematical analyses of 2010 FIFA world cup”, Applied Mathematics & Information Sciences, vol. 5, no. 2, pp 205–219, 2011

4. Yu Fujimoto, Hideitsu Hino, Noboru Murata, “An Estimation of Generalized Bradley-Terry Models Based on the em Algorithm”, Neural Computation, vol. 23, issue 6, pp 1623–1659, 2011

3. Hideitsu Hino, Noboru Murata, “A Conditional Entropy Minimization Criterion for Dimensionality Reduction and Multiple Kernel Learning”, Neural Computation, vol. 22, issue 11, pp 2887–2923, 2010

2. Hideitsu Hino, Yu Fujimoto, Noboru Murata, “A Grouped Ranking Model for Item Preference Parameter”, Neural Computation, vol. 22, issue 9, pp.2417–2451, 2010

1. Yoshio Uwano, Hideitsu Hino, Yasue Ishiwatari, “Certain integrable system on a space associated with a quantum search algorithm”, Physics of Atomic Nuclei, vol. 70, No. 4, pp.784–791, 2007

Refereed International Conferences

65. Tam Le, Truyen Nguyen, Hideitsu Hino, Kenji Fukumizu, ``An Efficient Orlicz-Sobolev Approach for Transporting Unbalanced Measures on a Graph'' [spotlight], The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025), San Diego, United States, 2-7 December, 2025

64. Hideaki Ishibashi, Kota Matsui, Kentaro Kutsukake, Hideitsu Hino, ``An (epsilon, delta)-accurate level set estimation with a stopping criterion'', European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2025 (ECML/PKDD2025), Porto, Portugal, 15 to 19 September, 2025, code available

63. Tam Le, Truyen Nguyen, Hideitsu Hino, Kenji Fukumizu, ``Scalable Sobolev IPM for Probability Measures on a Graph'', The 42nd International Conference on Machine Learning (ICML2025), Canada, July 13-19, 2025

62. Takahiro Kawashima, Hideitsu Hino, ``A Family of Distributions of Random Subsets for Controlling Positive and Negative Dependence'', The 28th International Conference on Artificial Intelligence and Statistics (AISTATS2025), Thailand, May 3 - 5, 2025

61. Takahiro Kawashima, Masanari Kimura, Tasuku Soma, Hideitsu Hino, ``Difference-of-submodular Bregman Divergence'', The Thirteenth International Conference on Learning Representations (ICLR2025), Singapore, April 24 – 28, 2025

60. Yusei Ito, Yasuo Takeichi, Hideitsu Hino, Kanta Ono, ``Optimal Spectroscopic Measurement Design: Bayesian Framework for Rational Data Acquisition'', AI for Accelerated Materials Design - NeurIPS2024 Workshop, Vancouver, Canada, 10-15, December, 2024

59. Thong Pham, Shohei Shimizu, Hideitsu Hino, Tam Le, ``Scalable Counterfactual Distribution Estimation in Multivariate Causal Models", 3rd conference on Causal Learning and Reasoning (CLeaR), Los Angeles, California, 1-3, April, 2024

58. Hideaki Ishibashi, Masayuki Karasuyama, Ichiro Takeuchi, Hideitsu Hino, ``A stopping criterion for Bayesian optimization by the gap of expected minimum simple regrets'', The 26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023), Valencia, Spain, 25-27 April, 2023

57. Toshimitsu Aritake, Hideitsu Hino, ``Domain Adaptation with Optimal Transport for Extended Variable Space”, International Joint Conference on Neural Networks (IJCNN), Padua, Italy, 18-23 July 2022

56. Hajime Ono, Kazuhiro Minami, Hideitsu Hino, ``One-bit Submission for Locally Private Quasi-MLE: Its Asymptotic Normality and Limitation'', The 25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022), 28-30 March, 2022

55. Takahiro Kawashima, Hayaru Shouno, Hideitsu Hino, ``Bayesian Dynamic Mode Decomposition with Variational Matrix Factorization", The Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI2021), 2-9, February, 2021, code available from here

54. Hideaki Ishibashi, Hideitsu Hino, ``Stopping criterion for active learning based on deterministic generalization bounds", The 23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020), Sicily, Italy, 3-5 June 2020

53. Shotaro Akaho, Hideitsu Hino, Noboru Murata, ``On a convergence property of a geometrical algorithm for statistical manifolds", the 26th International Conference on Neural Information Processing (ICONIP), Sydney Australia, 12-15 December 2019

52. Mizuo Nagayama, Toshimitsu Aritake, Hideitsu Hino, Takeshi Kanda, Takehiro Miyazaki, Masashi Yanagisawa, Shotaro Akaho, Noboru Murata, ``Sleep State Analysis using Calcium Imaging Data by Non-negative Matrix Factorization", 28th International Conference on Artificial Neural Networks (ICANN2019), 17--19, September 2019, Munich, Germany

51. Hayato Watanabe, Hideitsu Hino, Shotaro Akaho, Noboru Murata, ``Retrieved Image Refinement by Bootstrap Outlier Test", The 18th International Conference on Computer Analysis of Images and Patterns (CAIP2019), Salerno, Italy, 3--5, September 2019

50. Shin-ichiro Goto, Hideitsu Hino, ``Expectation variables on a para-contact metric manifold exactly derived from master equations", Geometric Science of Information, Toulouse, France, 27--29 August 2019

49. Yusuke Taguchi, Keisuke Kameyama, Hideitsu Hino, ``Active Learning with Interpretable Predictor", The 2019 International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, July 14-19, 2019, Source code available

48. Keita Nakamura, Sho Sonoda, Hideitsu Hino, Masahiro Kawasaki, Shotaro Akaho, Noboru Murata, ``Localizing Current Dipoles from EEG Data Using a Birth–Death Process", The 1st international workshop on Machine Learning for EEG Signal Processing (MLESP), Madrid, Spain, December 3-6, 2018

47. Keishi Sando, Shotaro Akaho, Noboru Murata, Hideitsu Hino, ``Information Geometric Perspective of Modal Linear Regression”, The 25th International Conference on Neural Information Processing (ICONIP2018), Siem Reap, Cambodia, December 13-16, 2018

46. Shotaro Akaho, Hideitsu Hino, Neneka Nara, Noboru Murata, ``Geometrical Formulation of the Nonnegative Matrix Factorization”, The 25th International Conference on Neural Information Processing (ICONIP2018), Siem Reap, Cambodia, December 13-16, 2018

45. Yuta Suzuki, Hideitsu Hino, Takafumi Hawai, Masato Kotsugi, Kanta Ono, ``Automated Lattice Constant Estimation of X-ray Diffraction by Ensemble Learning", The 5th International Conference on Electronic Materials and Nanotechnology for Green Environment (ENGE 2018), November 11 to 14, 2018 in Jeju, Korea

44. Tetsuro Ueno, Hideitsu Hino, Ai Hashimoto, Yasuo Takeuchi, Kanta Ono, ``Machine-Learning Assisted X-Ray Spectroscopy for High-Throughput Characterization of Magnetic Materials”, IEEE International Magnetics Conference (INTERMAG), Singapore, April 23–27, 2018

43. Tetsuro Ueno, Hideitsu Hino, Ai Hashimoto, Yasuo Takeuchi, Kanta Ono, ``High-throughput measurement of X-ray magnetic circular dichroism spectroscopy with machine learning”, IEEE International Magnetics Conference (INTERMAG), Dublin, Ireland, 24-28, April 2017

42. Lincon Sales de Souza, Hideitsu Hino, Kazuhiro Fukui, ``3D object recognition with enhanced Grassmann discriminant analysis”, The 13th Asian Conference on Computer Vision (ACCV2016) Workshop on Human Identification for Surveillance (HIS), Taipei, Taiwan, 20–24, November, 2016

41. Hideitsu Hino, Shotaro Akaho, Noboru Murata, ``An Entropy Estimator Based on Polynomial Regression with Poisson Error Structure”, The 23rd International Conference on Neural Information Processing (ICONIP2016), Kyoto, Japan, 16–21, October 2016

40. Hideitsu Hino, Ken Takano, Shotaro Akaho, Noboru Murata, ``Non-parametric e-mixture of density functions”, The 23rd International Conference on Neural Information Processing (ICONIP2016), Kyoto, Japan, 16–21, October 2016

39. Toshiyuki Kato, Hideitsu Hino, Noboru Murata, ``Doubly Sparse Structure In Image Super Resolution”, The 2016 IEEE Machine Learning for Signal Processing Workshop (MLSP2016), Vietri sul Mare, Salerno, Italy, 13–16, September 2016

38. Kensuke Koshijima, Hideitsu Hino, Noboru Murata, ``Change-Point Detection in a Sequence of Bags-of-Data (Extended Abstract)”, International Conference of Data Engineering (ICDE), TKDE poster track, Helsinki, Finland, 16-20, May 2016

37. Shohei Tanaka, Hideitsu Hino, Kazuhiro Fukui, ``Spotting Finger Spelled Words from Sign Language Video by Temporally Regularized Canonical Component Analysis”, The IEEE International Conference on Identity, Security and Behavior Analysis 2016, Miyagi, Japan, February 29– March 2, 2016

36. Takao Yoshinuma, Hideitsu Hino, Kazuhiro Fukui, ``Personal Authentication based on 3D Configuration of Micro-Feature Points on Facial Surface”, The 7the Pacific-Rim Symposium on Image and Video Technology, Auckland, New Zealand, November 23-27 2015

35. Takao Murakami, Atsunori Kanemura, Hideitsu Hino, ``Group Sparsity Tensor Factorization for De-anonymization of Mobility Traces”[Best Paper Award], The 14th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (IEEE TrustCom15), Helsinki, Finland, 20-22, August, 2015

34. Hideitsu Hino, ``Linear Discriminant Analysis with Adherent Regularization”,12th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2015), Liberec, Czech Republic, August 25– 28, 2015

33. Ken Takano, Hideitsu Hino, Yuki Yoshikawa, Noboru Murata, ``Patchworking Multiple Pairwise Distances for Learning with Distance Matrices”, 12th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA2015), Liberec, Czech Republic, August 25–28, 2015

32. Takamitsu Araki, Hideitsu Hino, Shotaro Akaho, ``A kernel method to extract common features based on mutual information”, The 21st International Conference on Neural Information Processing (ICONIP2014), Kuching, Malaysia, November, Lecture Notes in Computer Science 8835, pp. 26-34, 2014

31. Hideitsu Hino, Noboru Murata, ``A Non-Parametric Maximum Entropy Clustering” [Best Paper Award], International Conference on Artificial Neural Networks 2014(ICANN2014), Hamburg, Germany, September, Lecture Notes in Computer Science 8681, pp. 113–120, 2014, code available

30. Hideitsu Hino, Atsushi Noda, Masami Tatsuno, Shotaro Akaho, Noboru Murata, ``An Algorithm for Directed Graph Estimation”, International Conference on Artificial Neural Networks 2014(ICANN2014), Hamburg, Germany, September, Lecture Notes in Computer Science 8681, pp. 145-152, 2014

29. Yasuyuki Yamazaki, Hideitsu Hino, Kazuhiro Fukui, ``Sensing Visual Attention by Sequential Patterns”, International Conference on Pattern Recognition 2014(ICPR2014), Stockholm, Sweden, Augst. , pp. 483– 488, 2014

28. Bernardo Gatto, Hideitsu Hino, Kazuhiro Fukui, ``Block-based KOMSM for hand shape recognition with occlusion”, 20th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2014), February, (4 pages) 2014

27. Daisuke Takabayashi, Hideitsu Hino, Kazuhiro Fukui, ``Finger alphabets recognition with multi-depth images for developing their learning system”, 20th Korea-Japan Joint Workshop on Frontiers of Computer Vision (FCV2014), February, (4 pages) 2014

26. Chendra Hadi Suryanto, Hideitsu Hino, Kazuhiro Fukui, ``Combination of Multiple Distance Measures for Protein Fold Classification”, The 2nd IAPR Asian Conference on Pattern Recognition (ACPR2013), Okinawa, Japan, November, pp. 440–445, 2013

25. Hideitsu Hino, Tetsuji Ogawa, ``Integration of MKL-based and i-vector-based speaker verification by short utterances”, The 2nd IAPR Asian Conference on Pattern Recognition (ACPR2013), Okinawa, Japan, November, pp. 562–566, 2013

24. Hideitsu Hino, Nima Reyhan, ``Supervised Covariance Selection For Linear Discriminant Analysis”, The 2013 IEEE Machine Learning for Signal Processing Workshop (MLSP2013), Southampton, UK, September, (6 pages) 2013

23. Hideitsu Hino, ``Gaussian Multiple Kernel Learning with Entropy Power Inequality”, The 2013 IEEE Machine Learning for Signal Processing Workshop (MLSP2013), Southampton, UK, September, (6 pages) 2013

22. Hideitsu Hino, Jun Fujiki, Shotaro Akaho, Yoshihiko Mochizuki, Noboru Murata, ``Pairwise Similarity for Line Extraction From Distorted Images” The 15th International Conference on Computer Analysis of Images and Patterns (CAIP2013), York, UK, August, Lecture Notes in Computer Science 8048, pp. 250–257, 2013

21. Jun Fujiki, Shotaro Akaho, Hideitsu Hino, Noboru Murata ``Robust hypersurface fitting based on random sampling approximations” The 19th international conference on neural information processing(ICONIP2012), Doha, Qatar, November, Lecture Notes in Computer Science 7665, pp. 520–527, 2012

20. Haoyang Shen, Hideitsu Hino, Noboru Murata, Shinji Wakao, Yasuhiro Hayashi, ``Automatic Extraction of Basic Electricity Consumption Pattern in Households” International Conference on Renewable Energy Research and Applications(ICRERA), Nagasaki, November, (4 pages), 2012

19. Hideitsu Hino, Keigo Wakayama, Noboru Murata, ``Sliced Inverse Regression with Conditional Entropy Minimization” The 22nd International Conference on Pattern Recognition (ICPR2012), Tsukuba, Japan, November, pp. 1185–1188, 2012

18. Hideitsu Hino, Tetsuji Ogawa, ``An Improved Entropy-Based Multiple Kernel Learning” The 22nd International Conference on Pattern Recognition (ICPR2012), Tsukuba, Japan, November, pp. 1189–1192, 2012

17. Rui Rei, Joao P. Pedroso, Hideitsu Hino, Noboru Murata, ``A Tree Search approach to Sparse Coding”, Learning and Intelligent Optimization (LION2012), Paris, January, Lecture Notes in Computer Science 7219, pp. 472–477, 2012

16. Haoyang Shen, Hideitsu Hino, Noboru Murata, Shinji Wakao, ``Extraction of Basic Patterns of Household Energy Consumption”, The 10th International Conference on Machine Learning and Applications (ICMLA2011), Hawaii, USA, December, pp. 275–280, 2011

15. Haoyang Shen, Hideitsu Hino, Noboru Murata, Shinji Wakao, ``A measure of credibility of solar power prediction”, The 10th International Conference on Machine Learning and Applications (ICMLA2011), Hawaii, USA, December, pp. 286–291, 2011

14. Jun Fujiki, Shotaro Akaho, Hideitsu Hino, Noboru Murata, ``Calibration of radially symmetric distortion based on linearity in the calibrated image”, Workshop in ICCV2011: The 11th Workshop on Omnidirectional Vision, Camera Networks and Non-classical Cameras (Omnivis2011), Barcelona, Spain, November, pp. 288–295, 2011

13. Tetsuji Ogawa, Hideitsu Hino, Noboru Murata, Tetsunori Kobayashi, ``Speaker verification robust to talking style variation using multiple kernel learning based on conditional entropy minimization”, 12th Annual Conference of the International Speech Communication Association (Interspeech2011), Florence, Italy, August, pp. 2741–2744, 2011

12. Jun Fujiki, Shotaro Akaho, Hideitsu Hino, Noboru Murata, ``Robust hyperplane fitting based on k-th power deviation and alpha-quantile”, The 14th International Conference on Computer Analysis of Images and Patterns (CAIP2011. LNCS 6854, pp.278-285), Seville, Spain, August 2011

11. Nima Reyhani, Hideitsu Hino, Ricardo Vigario, ``New Probabilistic Bounds on Eigenvalues and Eigenvectors of Random Kernel Matrices”, The 27th Conference on Uncertainty in Artificial Intelligence (UAI2011. pp.627-634), Barcelona, Spain, July 2011

10. Hideitsu Hino, Noboru Murata, ``A Computationally Efficient Information Estimator for Weighted Data”, International Conference on Artificial Neural Networks (ICANN2011. LNCS vol.6792, pp.301-308), Espoo, Finland, June 2011

9. Tetsuji Ogawa, Hideitsu Hino, Nima Reyhani, Noboru Murata, Tetsunori Kobayashi, ``Speaker Recognition Using Multiple Kernel Learning Based on Conditional Entropy Minimization”, International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011. pp. 2204-2207), Prague, Czech Republic, May 2011

8. Yumi Usami, David G.Stork, Jun Fujiki, Hideitsu Hino, Shotaro Akaho, Noboru Murata, ``Improved Methods for Dewarping Images in Convex Mirrors in Fine Art: Applications to van Eyck and Parmigianino”, IS&T SPIE Electronic Imaging 2011, San Francisco, USA, January, (11 pages), 2011

7. Jun Fujiki, Yumi Usami, Hideitsu Hino, Shotaro Akaho, Noboru Murata, ``Estimation of a rotationally symmetric mirror shape from a frontal image of the mirror”, In Proc. of 25th International Conference of Image and Vision Computing New Zealand (IVCNZ2010), November, (6 pages), 2010

6. Hideitsu Hino, Nima Reyhani, Noboru Murata, ``Multiple Kernel Learning by Conditional Entropy Minimization”, The 9th International Conference on Machine Learning and Applications 2010 (ICMLA2010. pp.223-228), Washington D.C., USA, December 2010

5. Jun Fujiki, Hideitsu Hino, Yumi Usami, Shotaro Akaho, Noboru Murata ,``Self-calibration of radially symmetric distortion by model selection”, The 20th International Conference on Pattern Recognition (ICPR2010. pp.1812-1815), Istanbul, Turkey, August 2010

4. Yu Fujimoto, Hideitsu Hino, Noboru Murata, ``ITEM-USER PREFERENCE MAPPING WITH MIXTURE MODELS -Data Visualization for Item Preference-”, International Conference on Knowledge Discovery and Information Retrieval (KDIR2009), Madeira, Portugal, October, (4 pages), 2009

3. Hideitsu Hino, Yumi Usami, Jun Fujiki, Shotaro Akaho, Noboru Murata, ``Calibration of Radially Symmetric Distortion by Fitting Principal Component”, The 13th International Conference on Computer Analysis of Images and Patterns (CAIP2009. LNCS 5702, pp.149–156), Munster, Germany, September 2009

2. Hideitsu Hino, Noboru Murata, ``An Information Theoretic Perspective of the Sparse Coding”, 6th International Symposium on Neural Networks (ISNN2009. LNCS 5551, pp.84–93), Wuhan, China, May 2009

1. Hideitsu Hino, Yu Fujimoto, Noboru Murata, ``Item Preference Parameters from Grouped Ranking Observations”, 13-th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2009. LNAI 5476, pp.875–882), Bangkok, Thailand, April 2009

Unrefereed International Conferences and Workshops

34. Yuhei Takaya, Hideitsu Hino, Caio A. S. Coelho, ``Information-based probabilistic verification scores and predictability measures: Seasonal prediction examples”, 22nd Annual meeting of Asia Oceania Geosciences Society (AOGS 2025), Singapore, 27th July - 1st Aug., 2025

33. Keishi Sando, Hideitsu Hino, ``Complex non-backtracking matrix for directed graphs and its application to clustering'', IASC-ARS Interim Conference, Taipei, Taiwan, 13–14 December, 2024

32. Hideitsu Hino, Keisuke Yano, ``Information geometry of determinantal point process'', IASC-ARS Interim Conference, Taipei, Taiwan, 13–14 December, 2024

31. Yusei Ito, Yasuo Takeichi, Hideitsu Hino, Kanta Ono, ''Gigapixel X-ray Spectromicroscopy Data Analysis by Clustering”, 16th International Conference on X-Ray Microscopy (XRM 2024), Lund, Sweden, August 12– 16, 2024

30. Yusei Ito, Yasuo Takeichi, Hideitsu Hino, Kanta Ono, ''Optimal Spectromicroscopic Experimental Design for Massive Data Acquisition”, 16th International Conference on X-Ray Microscopy (XRM 2024), Lund, Sweden, August 12– 16, 2024

29. Hideitsu Hino, Masanari Kimura, ``A Geometrical Generalization of Covariate Shift'' [invited], International Conference on Information Geometry for Data Science (IG4DS) , Online, September 19–23, 2022

28. Masanari Kimura, Hideitsu Hino, ``Information Geometry of Dropout Training'', International Conference on Information Geometry for Data Science (IG4DS) , Online, September 19–23, 2022

27. Atsushi Nakao, Tatsu Kuwatani, Kenta Ueki, Kenta Yoshida, Taku Yutani, Hideitsu Hino, Shotaro Akaho, ``Relationship between maximum earthquake magnitudes and subduction-zone parameters revealed by multiple regression analysis and exhaustive variable selection'', Asia Oceania Geosciences Society 19th Annual Meeting, Online, August 01–05, 2022

26. Hideitsu Hino, Shin-itiro Goto, ``Symplectic integrator via contact geometry for Nesterov-type ODE'' [invited], Workshop on Functional Inference and Machine Intelligence (FIMI), Online, 29-31, 2022

25. Hideitsu Hino "Modal Principal Component Analysis", ISM-Bristol Joint Seminar: Methodologies and Applications of Geometric Data Analysis, Sept. 24, online, 2020

24. Yuta Suzuki, Hideitsu Hino, Takafumi Hawai, Kotaro Saito, Kanta Ono, ”Machine learning approach for on-the-fly crystal system classification from powder x-ray diffraction pattern”, 2020 TMS Annual Meeting & Exhibition, San Diego, California, USA, February 23-27, 2020

23. Hiromichi Nagao, Shin-ichi Ito, Kei Hasegawa, Masayuki Kano, Masato Okada, Hideitsu Hino, Kenji Nagata, Naoshi Hirata, "Implementation of Replica Exchange Monte Carlo on 4DVar for Global Optimization", AGU Fall Meeting 2019, December 10, 2019

22. Kenta Ueki, Hideitsu Hino, Tatsu Kuwatani, "Feature Selection of Magmatic Tectonic Settings Based on Sparse Multinomial Regression", 15th Annual Meeting, Asia Oceania Geosciences Society (AOGS2019), Singapore, July 28-Augst 2, 2019

21. Hideitsu Hino, "A Higher Order Local Intrinsic Dimension Estimator by Regression Analysis", 3rd International Conference on Econometrics and Statistics (EcoSta2019), Taiwan, June 25-27, 2019

20. Hideitsu Hino, "Fused Sparse Transition Probability Matrix Estimation", The 4th ISM-ZIB-IMI MODAL Workshop on Mathematical Optimization and Data Analysis, Tokyo, March 27-29, 2019

19. Hideitsu Hino, "Localizing and Determining the Number of Dipoles from EEG Signals by Particle Filter", Workshop on Computational Statistics and Machine Learning, Tokyo, 15-16 October, 2018

18. Yuta Suzuki, Hideitsu Hino, Yasuo Takeichi, Takafumi Hawai, Masato Kotsugi, Kanta Ono, “Machine Learning-based Crystal Structure Prediction for X-Ray Microdiffraction”, 14th International Conference on X-Ray Microscopy (XRM 2018), Saskatchewan, Canada, August 19– 24, 2018

17. Yuta Suzuki, Hideitsu Hino, Tetsuro Ueno, Yasuo Takeichi, Masato Kotsugi, Kanta Ono, ''Extraction of Physical Parameters from X-ray Spectromicroscopy Data Using Machine Learning”, 14th International Conference on X-Ray Microscopy (XRM 2018), Saskatchewan, Canada, August 19– 24, 2018

16. Tetsuro Ueno, Hideitsu Hino, Kanta Ono, "Optimal Design of Experiment for X-Ray Spectromicroscopy by Machine Learning", 14th International Conference on X-Ray Microscopy (XRM 2018), Saskatchewan, Canada, August 19– 24, 2018

15. Yuta Suzuki, Hideitsu Hino, Masato Kotsugi, Kanta Ono, “Classification of Crystal Structure from X-ray Diffraction Patterns using Machine Learning”, The 13th International Conference on Synchrotron Radiation Instrumentation (SRI 2018), Taipei, Taiwan, June 10–15, 2018.

14. Yuta Suzuki, Hideitsu Hino, Masato Kotsugi, Kanta Ono, “Estimation of Physical Parameters using Dimensionality Reduction of X-Ray Absorption Spectra”, The 13th International Conference on Synchrotron Radiation Instrumentation (SRI 2018), Taipei, Taiwan, June 10–15, 2018

13. Tetsuro Ueno, Hideitsu Hino, Kanta Ono, “Efficiency Improvement of X-Ray Spectroscopy using Machine Learning”, International Conference on Magnetism (ICM2018), Sanfrancisco, U.S.A., July, 15–20, 2018

12. Ryoko Nakata, Takane Hori, Hideitsu Hino, Tatsu Kuwatani, Shoichi Yoshioka, Masato Okada, “Geodetic data inversion for spatial distribution of long-term slow slip events beneath the Bungo Channel, southwest Japan, using sparse modelling”, 15th Annual Meeting, Asia Oceania Geosciences Society (AOGS2018), Honolulu, Hawaii, June 03–08, 2018

11. Kenta Ueki, Hideitsu Hino, Tatsu Kuwatani, “Geochemical Discrimination Using Machine Learning: Magmatic Tectonic Settings and Geochemical Signatures”, 15th Annual Meeting, Asia Oceania Geosciences Society (AOGS2018), Honolulu, Hawaii, June 03–08, 2018

10. Taishi Iwasaki, Hideitsu Hino, Masami Tatsuno, Shotaro Akaho, Noboru Murata, “Estimation of neural connections from partially observed neural spikes”, Society for Neuroscience 2017 Annual Meeting, 11 – 15 November 2017 Washington D.C., United States

9. Takane Hori, Ryoko Nakata, Hideitsu Hino, Tatsu Kuwatani, Shoichi Yoshioka, Masato Okada, “Geodetic inversion for spatial distribution of slow earthquakes under sparsity constraints”, International Meeting on High-Dimensional Data Driven Science (HD3-2017) Kyoto, Japan, September 9–13, 2017

8. Shotaro Akaho, Hideitsu Hino, Neneka Nara, Ken Takano, Noboru Murata, “A Projection Algorithm Based on the Pythagorian Theorem and its Applications”, Information Geometry and its Applications IV (IGAIA IV), Liblice, Czech Republic, 13-17 June, 2016

7. Shotaro Akaho, Sho Higuchi, Taishi Iwasaki, Hideitsu Hino, Masami Tatsuno, Noboru Murata, “Graph Structure Modeling for Multi-neuronal Spike Data”, International Meeting on High-Dimensional Data Driven Science (HD3-2015) Kyoto, Japan, December 14–17, 2015

6. Hideitsu Hino, “Information and entropy estimators for machine learning and pattern recognition”, The 3nd Institute of Mathematical Statistics Asia Pacific Rim Meeting, Taiwan, June, 2014

5. Noboru Murata, Kensuke Koshijima, Hideitsu Hino, “Distance-based Change-Point Detection with Entropy Estimation”, The Sixth Workshop on Information Theoretic Methods in Science and Engineering (WITMSE2013), 26-29 August 2013, Tokyo, Japan

4. Noboru Murata, Sho Sonoda, Hideitsu Hino, Hiroshi Kitada, Manabu Kano, “Sensitivity Analysis for Controlling Liquid Steel Temperature in Tundish” 2012 IFAC Workshop on Automation in the Mining, Mineral and Metal Industries, Gifu, Japan, September, 2012

3. Hideitsu Hino, Kazuki Miura, Noboru Murata, “Weight Optimization for Ensemble of Learners by Information Minimization”, The 2nd Institute of Mathematical Statistics Asia Pacific Rim Meeting, Japan, July, 2012

2. Rui Rei, Joao P. Pedroso, Hideitsu Hino, Noboru Murata, “A Tree Search approach to Sparse Coding”, 17th edition of the Portuguese Conference on Pattern Recognition, Porto, Portuguese, October, 2011

1. Yu Fujimoto, Hideitsu Hino, Noboru Murata, “An Estimation Method for Bradley-Terry and its Related Models based on the Bregman Divergence”, Learning Workshop 2010 (Computational and Biological Learning Society), Utah, United States, April, 2010.

Domestic Workshop

163. 石峯拓海，日野英逸，横井祥，``言語モデルの最終隠れ状態のソフト分割可能な単体複体としての分析", 第28回情報論的学習理論ワークショップ（IBIS2025），沖縄，2025/11/12-14

162. 岩崎喬一，Le Tam，日野英逸，``ソボレフ曲率とその応用", 第28回情報論的学習理論ワークショップ（IBIS2025），沖縄，2025/11/12-14

161. 三戸圭史，Le Tam，日野英逸，``木構造によるCategorical Wasserstein Weisfeiler-Lehman Graph Kernelの高速化", 第28回情報論的学習理論ワークショップ（IBIS2025），沖縄，2025/11/12-14

160. 小野佑太朗，谷垣俊明，日野英逸，五十嵐康彦，``電子線ホログラフィーによる電荷量解析における必要な計測フレーム数の統計的推定''，日本顕微鏡学会第81回学術講演会，福岡，2025/06/09-11

159. 川島貴大，木村正成，相馬輔，日野英逸，``集合間Bregmanダイバージェンスと置換不変NNによるその学習'', [人工知能学会全国大会優秀賞] 第39回人工知能学会全国大会，大阪，2025/05/27 - 30

158. 河田將翔，新原隆史，日野英逸，``主成分分析による月試料の分類の試み''，日本地球惑星科学連合2025年大会，千葉，2025/05/25-30

157. 桑谷立，日野英逸，西川遥，赤穂昭太郎，``黒潮流軸の類似検索を用いたデータ駆動型軽石漂流推移予測：伊豆諸島明神礁への適用''，日本地球惑星科学連合2025年大会，千葉，2025/05/25-30

156. 加藤広野，披田野清良，村上隆夫，日野英逸，``対照損失および防御ノイズ付与を伴うファインチューニングによるFew-shot画像分類モデルの保証付き頑健性の向上''，第42回　暗号と情報セキュリティシンポジウム（SCIS2025)，福岡，2025/01/28 - 31

155. 五十嵐康彦，永村直佳，関根正大，吹留博一，日野英逸，岡田真人，``スパースコーディングに基づくマルチフレーム超解像手法による効率的な走査型光電子顕微画像計測''，第38回日本放射光学会年会・放射光科学合同シンポジウム，茨城，2025/01/10 - 12

154. 川島貴大，日野英逸，``引力と斥力を制御可能なべき集合上の分布族’’，[優秀プレゼンテーション賞] 第27回情報論的学習理論ワークショップ（IBIS2024），埼玉，2024/11/4-7

153. 三戸圭史，日野英逸，``有向グラフでの複素Non-backtracking行列とクラスタリングへの応用''，第27回情報論的学習理論ワークショップ（IBIS2024），さいたま，2024/11/4-7

152. 川島貴大，日野英逸，``引力と斥力を制御可能なべき集合上の新たな分布族の提案''，2024年度統計関連学会連合大会，東京，2024/09/01 - 05

151. 岩崎喬一，日野英逸，``t-SNEの加速と力学系'', [研究会賞ファイナリスト] 第54回情報論的学習理論と機械学習研究会(IBISML), 沖縄，2024/6/21

150. 有竹俊光，日野英逸，``グラフ上の距離を用いたFused Gromov-Wasserstein最適輸送による変数の拡張に対するドメイン適応''，第38回人工知能学会全国大会，静岡，2024/05/29

149. 石橋英朗，松井孝太，沓掛健太郎，日野英逸，``レベルセット推定の停止基準''，第38回人工知能学会全国大会，静岡，2024/05/29

148. 伊藤優成，武市泰男，日野英逸，小野寛太，``X線吸収分光顕微鏡計測に対する計測最適化''，第71回応用物理学会春季学術講演会，東京，2024/3/22-25

147. 伊藤優成，武市泰男，日野英逸，小野寛太，``XAFSスペクトルの不確実性の定量化と計測最適化''，第37回日本放射光学会年会・放射光科学合同シンポジウム，兵庫，2024/1/12

146. 佐藤拓人, 日野英逸, 日下博幸，``動的モード分解による都市ヒートアイランド循環とサーマルの分離", 第37回数値流体力学シンポジウム（CFD37）, 愛知, 2023/12/15 - 12/17

145. 有竹俊光，日野英逸，``グラフ上の距離を用いたFused Gromov-Wasserstein最適輸送による変数の拡張に対するドメイン適応''，第26回情報論的学習理論ワークショップ（IBIS2023），福岡，北九州，2022/10/31

144. 木村正成，川島貴大，相馬輔，日野英逸，``Neural Submodular Bregman Divergences''，第26回情報論的学習理論ワークショップ（IBIS2023），福岡，北九州，2023/10/30

143. 伊藤優成，武市泰男，日野英逸，小野寛太，``X線吸収分光スペクトルの不確実性の定量化と計測最適化への応用''，第84回応用物理学会秋季学術講演会，熊本，2023/9/20

142. 宮崎峻弘，上田壮志，坂本航太郎，日野英逸，石川有紀子，柳沢正史，``損傷脳領域の機能代償を司る大脳皮質運動野再構築と睡眠が与える影響の解明''，日本睡眠学会第45回定期学術集会，神奈川，2023/09/15 - 09/17

141. 玉野浩嗣，日野英逸，持橋大地，``多次元項目応答理論における非補償型−補償型の誤特定下での推定分散について''，日本行動計量学会第51回大会，東京，2023/08/28 - 08/31

140. 川島貴大，日野英逸，``MMアルゴリズムによる行列式点過程の学習''，第50回IBISML研究会，沖縄，2023/06/29 - 07/011

139. 佐川正悟，日野英逸，``生成モデルを活用する段階的ドメイン適応''，第37回人工知能学会全国大会，熊本，2023/06/07-06/09

138. 伊藤優成，武市泰男，日野英逸，小野寛太，``機械学習を用いたギガピクセルイメージングXAFSデータの解析''，第70回応用物理学会春季学術講演会，東京，2023/3/17

137. 坂本航太郎，有竹俊光，日野英逸，``相互作用情報量による能動学習''，第25回情報論的学習理論ワークショップ（IBIS2022），つくば，茨城，2022/11/21

136. 有竹俊光，日野英逸，``エントロピー正則化付き最適輸送を用いた漸進的ラベル伝播法''，第25回情報論的学習理論ワークショップ（IBIS2022），つくば，茨城，2022/11/21

135. 関根正大，永村直佳，日野英逸，岡田真人，五十嵐康彦，``スパースモデリングを用いたマルチフレーム超解像による放射光顕微分光画像への展開''，第25回情報論的学習理論ワークショップ（IBIS2022），つくば，茨城，2022/11/21

134. 佐川正悟，日野英逸，``Normalizing Flowを用いた段階的ドメイン適応''，第25回情報論的学習理論ワークショップ（IBIS2022），つくば，茨城，2022/11/21

133. 川島貴大，日野英逸，``低ランク行列式点過程の最尤推定''，第25回情報論的学習理論ワークショップ（IBIS2022），つくば，茨城，2022/11/21

132. 横山勇気，桑谷立，寺岡毅，松本純也，日野英逸，塩谷智基，``順序ロジスティック回帰分析を用いた道路橋の健全度予測モデルの開発''，土木学会全国大会, 2022/09/12 - 16，京都

131. 佐川正悟，日野英逸，``Multifidelity能動学習を用いた段階的ドメイン適応", [研究会賞ファイナリスト] 第46回IBISML研究会，2022/06/27 - 29, 沖縄

130. 上野哲郎，石橋英朗，日野英逸，小野寛太，``能動学習によるスペクトル計測の自動停止''，2022年度人工知能学会全国大会（第36回），2022/06/14-17，京都

129. 坂本航太郎，佐藤怜，秋本洋平，白川真一，石橋英朗，日野英逸，``ニューラルアーキテクチャサーチの最適停止''，2022年度人工知能学会全国大会（第36回），2022/06/14-17，京都

128. 中尾篤史，桑谷立，上木賢太，吉田健太，油谷拓，日野英逸，赤穂昭太郎，``沈み込むプレートのペネトレーション/スタグネーションと沈み込み帯パラメタを関係づける回帰分析とモデル選択'', 日本地球惑星連合大会，2022/5/22，オンライン

127. 上田壮志, 宮崎峻弘, 坂本航太郎, 日野英逸, 柳沢正史，''一次運動野機能的ネットワーク構造が示唆する休息と徐波睡眠の類似性", Neuro2022, 2022/06/30 - 7/3, 沖縄

126. 上田壮志, 宮崎峻弘, 坂本航太郎, 日野英逸, 柳沢正史，"Distinct network structures emerge in the primary motor cortex during active and quiet wake"，第99回日本生理学会大会, 2022/03/16–18，仙台，宮城

125. 木村正成，日野英逸，"共変量シフトの情報幾何"，第44回IBISML研究会，2022/01/17-18，オンライン

124. 有竹俊光，日野英逸，"変数の拡張に対する最適輸送を用いたドメイン適応"，[2021年度IBISML研究会賞] 第44回IBISML研究会，2022/01/17-18，オンライン

123. 川島貴大，日野英逸，"ガウス過程Koopmanモード分解"，第24回情報論的学習理論 (IBIS) ワークショップ，2021/11/10-13，オンライン

122. 五十嵐康彦，永村直佳，日野英逸，岡田真人，“スパースモデリングを用いた超解像によるマルチフレーム顕微分光画像への展開“，2021年日本表面真空学会，2021/11/4，オンライン

121. 中尾篤史，桑谷立，上木賢太，吉田健太，油谷拓，日野英逸，赤穂昭太郎，"地震の最大マグニチュードと沈み込み帯パラメタを関係づける回帰分析"，日本地震学会2021年度秋季大会，2021/10/15，オンライン

120. 上田壮志, 宮崎峻弘, 坂本航太郎, 日野英逸, 柳沢正史, "安静時とノンレム睡眠時の大脳皮質局所ネットワーク構造は類似である", 第31回日本神経回路学会全国大会（JNNS2021）, 2021年9月21–23日，オンライン

119. 上田壮志, 宮崎峻弘, 坂本航太郎, 日野英逸, 柳沢正史, "一次運動野の機能的ネットワークはquiet wakeとnon-REM睡眠時で類似の構造をもつ", 第15回Motor Control研究会, 2021/9/9 - 11，オンライン

118. 五十嵐康彦，永村直佳，日野英逸，岡田真人，"スパースモデリングを用いた超解像によるマルチフレーム顕微分光画像への展開"，第77回日本顕微鏡学会学術講演会，2021/06/14, オンライン

117. 桑谷立，日野英逸，永田賢二，川島貴大，鳥海光弘，岡田真人，"ベイズ計測の空間解像度"，日本地球惑星科学連合2021年大会，2021/06/03，オンライン

116. 日野英逸，"ベイズ的動的モード分解"，[招待講演] 日本地球惑星科学連合2021年大会，2021/06/03，オンライン

115. 伊藤龍之介，亀山啓輔，日野英逸，"異なる倍率の走査型電子顕微鏡像を用いた金属材料の解析"，パターン認識・メディア理解研究会 (PRMU)，2020/03/16 - 17，京都

114. 三戸圭史，日野英逸，"最頻値推定量を用いた主成分分析の提案"，[研究会賞ファイナリスト]第39回IBISML研究会，2020/03/10-11, 京都

113. 田口優介，日野英逸，亀山啓輔，“強化学習を用いた複数データ選択のための能動学習”，第38回IBISML研究会，2020/01/09，東京

112. 有竹俊光，日野英逸，並木繁行，浅沼大祐，廣瀬謙造，村田昇，“深層ニューラルネットワークを用いた多焦点顕微鏡のリアルタイム3次元局在化”，第38回IBISML研究会，2020/01/09，東京

111. 後藤振一郎，日野英逸，"マスター方程式の離散幾何学--拡散方程式の厳密な導出", 第25回交通流と自己駆動粒子系のシンポジウム, 2019/12/06, 愛知

110. 川島貴大，日野英逸，"BICによるProbabilistic DMDのモード数選択"，第22回情報論的学習理論 (IBIS) ワークショップ，2019/11/19-22，愛知

109. 石橋英朗，日野英逸，"能動学習の停止基準"，第22回情報論的学習理論 (IBIS) ワークショップ，2019/11/19-22，愛知

108. 日野英逸，"能動学習とベイズ最適化"，日本表面真空学会学術講演会，2019/10/28，茨城

107. 嶋野岳人，日野英逸，安田敦，井口正人，上木賢太，桑谷立，”火山灰測色値と地球物理データとの時系列相関解析 – 桜島昭和火口 2009-2015 年活動について–”，2019年度秋季大会，2019/09/25-30，兵庫

106. Ryoko Nakata, Hideitsu Hino, Tatsu Kuwatani, Takahiro Akiyama, Shoichi Yoshioka, Masato Okada, Takane Hori, "Spatial distribution of long-term slow slip event from 2018 to 2019 beneath the Bungo Channel under sparsity constraints", スロー地震国際合同研究集会 (Slow Eq WS 2019), 2019/09/21-23, 2019

105. 高畠卓也，日野英逸，山本誠，酒本晋太郎，``ベイズ最適化を用いた熱源システムの最適設定値探索アルゴリズムの研究”，2019年度空気調和・衛生工学会大会，2019/09/18 - 20，北海道

104. 日野英逸，``統計学の基礎と考え方”, (チュートリアル講演)日本学術振興会シリコン超集積システム第 165 委員会, 2019/08/23, 大阪

103. 永山瑞生，有竹俊光，日野英逸，上田壮志，宮崎峻弘，柳沢正史，赤穂昭太郎，村田昇，``非負値行列因子分解を用いたカルシウムイメージングデータからの睡眠状態解析"，第37回情報論的学習理論研究会（IBISML研究会），2019/6/18，沖縄

102. 日野英逸，``ガウス過程回帰の基礎と計測への応用"，天文学におけるデータ科学的方法，2019/05/28, 東京 [招待講演]

101. Ryoko Nakata, Hideitsu Hino, Tatsu Kuwatani, Takahiro Akiyama, Shoichi Yoshioka, Masato Okada, Takane Hori, ``Spatial distribution of slow slip events off the Boso peninsula from 1996 to 2018 under sparsity constraints", 日本地球惑星科学連合大会, 2019/05/26 - 05/30, 千葉

100. 日野英逸，``ガウス過程回帰による能動学習", 量子ビームサイエンスフェスタ，2019/03/12，つくば，茨城

99. 鈴木雄太，日野英逸，小嗣真人，小野寛太，``回折パターンデータベースの構築と機械学習による結晶構造予測"，量子ビームサイエンスフェスタ，2019/03/12，つくば，茨城

98. 鈴木雄太，日野英逸，小嗣真人，小野寛太，``X線回折パターンからの結晶構造予測"，第66回応用物理学会春季学術講演会，2019/03/09，東京

97. 石丸貴大，金子涼佑，合原一究，織田隆治，日野英逸，河辺徹，``カエルロボットの開発および野生のカエルによる行動実験への応用"，[発表論文賞大会委員長賞] 日本比較生理生化学会第40回大会，2018/11/23，神戸，兵庫

96. 村上隆夫，日野英逸，佐久間淳，``局所型差分プライバシーを満たす小規模データからの分布推定に向けて"，第8回バイオメトリクスと認識・認証シンポジウム(SBRA2018)，2018/11/20-21, 東京

95. 後藤振一郎，日野英逸，``熱浴法の幾何学的描像"，[ベストプレゼンテーション賞ファイナリスト]，第21回情報論的学習理論 (IBIS) ワークショップ，2018/11/4-7，北海道

94. 和田尭，日野英逸，``多目的最適化と多点探索のためのベイズ最適化"，第21回情報論的学習理論 (IBIS) ワークショップ，2018/11/4-7，北海道

93. 五十嵐里紗，日野英逸，赤穂昭太郎，村田昇，``Weighted Jensen-Shannon divergence規準のランダムフォレストを用いた条件付き分布の推定"，第21回情報論的学習理論 (IBIS) ワークショップ，2018/11/4-7，北海道

92. 布施拓馬，日野英逸，赤穂昭太郎，村田昇，``構造が時間に依存して変化するデータの埋め込み"，第21回情報論的学習理論 (IBIS) ワークショップ，2018/11/4-7，北海道

91. 佐藤拓人, 日下博幸, 日野英逸, ``熱中症患者搬送者数予測モデルのための温熱要素の調査"[優秀発表賞], 第57回日本生気象学会大会, 京都, 2018/10/27

90. 田口優介，亀山啓輔，日野英逸，``説明可能な能動的サンプル選択”，[研究会賞ファイナリスト]第34回情報論的学習理論と機械学習研究会，2018/09/21，福岡

89. 長尾大道, 日野英逸，``情報計測の高度化に向けた統計的・機械学習的アプローチの今後の展望”，2018年度統計関連学会連合大会，2018/09/11，東京

88. 上木賢太, 日野英逸, 桑谷立，``スパース回帰を用いた全地球マグマ化学組成の分類と特徴抽出”，2018年度統計関連学会連合大会，2018/09/11，東京

87. 上野哲朗, 日野英逸, 小野寛太，``ガウス過程回帰による X 線スペクトル測定の効率化”，2018年度統計関連学会連合大会，2018/09/11，東京

86. 後藤振一郎, 日野英逸，``あるマスター方程式から導出される期待値方程式に対する接触幾何学的記述”，日本応用数理学会2018年度年会，2018/09/03，愛知

85. 佐藤拓人, 日下博幸, 日野英逸，``熱中症患者搬送者数予測に資する温熱要素の同定”，日本ヒートアイランド学会第13回全国大会 2018/08/25，大阪

84. 日野英逸，``統計学の基礎と考え方”, (チュートリアル講演) 日本学術振興会シリコン超集積システム第165委員会, 2018/08/24, 東京

83. 中村圭太，園田翔，日野英逸，川崎真弘，村田昇, ``生成・消滅過程に基づく EEG データの電流ダイポール推定”, 第33回情報論的学習理論と機械学習研究会 (IBISML), 2018/06/13 - 06/15, 沖縄(沖縄科学技術大学院大学)

82. 田中大，日野英逸，並木繁行，浅沼大祐，廣瀬謙造，村田昇, ``畳み込みニューラルネットワークを用いた顕微鏡画像の3次元超解像”, 第 33 回情報論的学習理論と機械学習研究会 (IBISML), 2018/06/13 - 06/15, 沖縄(沖縄科学技術大学院大学)

81. 日野英逸[招待講演], ``統計的外れ値検知とその応用”, 日本地球惑星科学連合大会, 2018/05/22, 千葉

80. 上木賢太，日野英逸，桑谷立, ``機械学習を用いた様々なテクトニクス場のマグマ化学組成の分類と特徴量抽出”, 日本地球惑星科学連合大会, 2018/05/22, 千葉

79. 中田令子，日野英逸，桑谷立，田中もも，吉岡祥一，岡田真人，堀高峰, ``疎性モデリングで得られた豊後水道長期的スロースリップイベントのすべり分布(2)”, 日本地球惑星科学連合大会, 2018/05/23, 千葉

78. 上野哲郎，日野英逸，小野寛太, ``機械学習による X 線スペクトル測定の効率化”, 第65回応用物理学会春季学術講演会, 2018/03/17 - 03/20, 東京(早稲田大学西早稲田キャンパス)

77. 鈴木雄太，日野英逸，小嗣真人，小野寛太, ``スペクトルの次元削減によるデータ可視化および物理量推定の検討”, 第65回応用物理学会春季学術講演会, 2018/03/17 - 03/20, 東京(早稲田大学西早稲田キャンパス)

76. 川崎真弘，宮内英里，合原一究，安東弘泰，日野英逸, ``ヒトの脳内状態の切り替えに関する脳波リズム”, 日本認知科学会知覚と行動モデリング(P&P)研究分科会, 2018/03/15, 東京(筑波大学東京キャンパス)

75. 三戸圭史，赤穂昭太郎，村田昇，日野英逸, ``最頻値線形回帰の情報幾何”, 第32回情報論的学習理論と機械学習研究会 (IBISML), 2018/03/05 - 03/06, 九州(九州大学西新プラザ)

74. 渡邊隼人，日野英逸，赤穂昭太郎，村田昇, ``ブートストラップ分布に基づく外れ値検定”, 第32回情報論的学習理論と機械学習研究会 (IBISML), 2018/03/05 - 03/06, 九州 (九州大学西新プラザ)

73. 河合祐輔，日野英逸，建部修見, ``pbdMPIを用いたエントロピー推定プログラムの並列化と性能評価”, 情報処理学会第163 回ハイパフォーマンスコンピューティング研究会, 愛媛, 2 月 28 日-3 月 2 日, 2018

72. 日野英逸, ``機械学習のエッセンス:イマドキの方法を学ぶ前に”, (チュートリアル講演) 第5回コミュニケーションクオリティ (CQ) 基礎講座ワークショップ, 2018/01/20, 東京

71. 鈴木雄太，小嗣真人，日野英逸，小野寛太, ``X 線吸収スペクトルからの物理量の自動抽出”, 日本放射光学会年会・放射光科学合同シンポジウム, 2018/01/08 - 01/10, つくば

70. 上野哲郎，日野英逸，橋本愛，武市泰男，小野寛太, ``機械学習による X 線吸収スペクトル測定の高効率化”, 日本放射光学会年会・放射光科学合同シンポジウム, 2018/01/08 - 01/10, つくば

69. 日野英逸, ``スパースモデリング再入門と深化”, スパースモデリングの深化と高次元データ駆動科学の創成チュートリアル, 2017/12/17, 東京

68. 赤穂昭太郎，岩崎泰士，日野英逸，龍野正実，村田昇, ``多点計測スパイクデータに基づく神経細胞間の結合推定”, 第 27回日本神経回路学会全国大会，2017/09/20 - 09/22, 福岡

67. Teturo Ueno, Hideitsu Hino, Ai Hashimoto, Yasuo Takeichi, Kanta Ono, ``High-throughput experiment of X-ray magnetic circular dichroism spectroscopy with machine learning”, 第 41 回日本磁気学会学術講演会，2017/09/19 - 09/22, 福岡

66. 宮本英昭，新原隆史，洪鵬，日野英逸, ``Relationship between reflectance spectra of meteorites and asteroids visualized by the correlation distance and t-SNE,” 日本地球惑星科学連合大会, 2017/05/20 - 05/25, 千葉

65. Kenta Ueki, Hideitsu Hino, ``Sparse feature selection for clustering and sample-wise distance, with application to geochemical data,” 日本地球惑星科学連合大会, 2017/05/20 - 05/25, 千葉

64. Rina Noguchi, Kei Kurita, Hideitsu Hino, Nobuo Geshi, ``Statistical classification of tephra from rootless eruptions”, 日本地球惑星科学連合大会, 2017/05/20 - 05/25, 千葉

63. Rina Noguchi, Hideitsu Hino, ``粒子形状に基づいた火砕物のクラスター分析手法の検討”, 日本地球惑星科学連合大会, 2017/05/20 - 05/25, 千葉

62. 村上隆夫，兼村厚範，日野英逸，``グループスパーステンソル分解とその位置情報プライバシー攻撃への応用"，第 6 回バイオメトリクスと認識・認証シンポジウム (SBRA2016)，2016/11/16–2016/11/17，芝浦工業大学，東京

61. 日野英逸, 藤木淳，赤穂昭太郎，村田昇，``重回帰を用いた高次局所潜在的次元推定"，第 26 回情報論的学習理論と機械学習研究会 (IBISML), 2016/09/05 - 09/06, 富山

60. 日野英逸，``スパースモデリングと正則化回帰"，第 35回日本医用画像工学会大会シンポジウム「医用画像工学におけるスパースモデリング」, 2016/07/21 - 07/23, 千葉大学，千葉

59. 中田令子，日野英逸，桑谷立，岡田真人，堀高峰，``疎性モデリングを用いたスロー地震のインバージョン", 日本地球惑星科学連合大会, 2016/05/22 - 05/26, 千葉

58. 日野英逸，赤穂昭太郎，村田昇，``確率質量関数の二次展開とポアソン誤差構造に基づくエントロピー推定", 第24回情報論的学習理論と機械学習研究会 (IBISML), 2016/03/17 - 03/18, 東京

57. 奈良寧々花，高野健，日野英逸，赤穂昭太郎，村田昇，``非負値行列分解の情報幾何", 第18 回情報論的学習理論ワークショップ (IBIS2015), 2015/11/25 - 11/27, 茨城

56. 高野健，日野英逸，赤穂昭太郎，村田昇，``ノンパラメトリックモデルのe混合推定とその応用", 第18回情報論的学習理論ワークショップ (IBIS2015), 2015/11/25 - 11/27, 茨城

55. 日野英逸，``機械学習の問題意識と問題設定", (チュートリアル講演) 電子情報通信学会知的環境とセンサネットワーク研究会シンポジウム「知的環境と機械学習」，2015/10/28，東京

54. 近藤祐，日野英逸，原一之，``Model Compression の実験的評価一真のモデルが既知の場合一", 日本神経回路全国大会 (JNNS2015), 2015/09/02 - 04，東京

53. 日野英逸，``正規モデルとFisher 判別モデルを結ぶ正則化線形判別分析"[研究会賞], パターン認識・メディア理解研究会 (PRMU), 2015/06/18 - 19，新潟

52. 加藤利幸，日野英逸，村田昇，``二重スパース性に基づくマルチフレーム超解像", パターン認識・メディア理解研究会 (PRMU), 2015/06/18 - 19，新潟

51. 日野英逸, ``スパースコーディングの数理と応用" (チュートリアル講演) 日本ロボット学会第 90 回ロボット工学セミナーロボットビジョンのための画像処理技術，2015/5/14，東京

50. 日野英逸, ``機械学習の考え方~データからの知識発見に向けて~(チュートリアル講演)”, 2015 年電子情報通信学会総合大会知的環境とセンサネットワーク研究会チュートリアルセッション，2015/3，滋賀

49. 菊池優介，日野英逸，福井和広, ``距離画像から得られる形状空間に基づく手の形状識別と姿勢推定”, コンピュータビジョンとイメージメディア研究会 (CVIM2015/3), 201503, 宮城

48. 日野英逸, ``スパースモデリングに基づく点過程データ解析”, 東京大学地震研究所共同利用研究会「室内実験と数値実験から探る地震活動の物理」，2015/3，東京

47. 日野英逸，越島健介，村田昇, ``単回帰に基づく微分エントロピー推定量”, 大規模統計モデリングと計算統計研究会，2015/2，東京

46. 千葉智暁，日野英逸，赤穂昭太郎，村田昇, ``時間推移する定常分布の潜在構造モデル化”, 第 101回数理モデル化と問題解決研究会 (MPS101), 2014/12，奈良

45. 日野英逸，越島健介，村田昇, ``確率質量関数の二次展開と単回帰に基づくエントロピー推定”, 情報論的学習理論と機械学習研究会 (IBISML), 2014/11, 愛知

44. 日野英逸, ``スパースモデリングの基礎(チュートリアル講演)”, 第 17 回画像の認識・理解シンポジウム (MIRU2014), 2014/07, 岡山

43. 樋口翔，日野英逸，龍野正美，村田昇, ``重み付き有向グラフモデリングによるスパイクデータ解析”[優秀研究賞]，ニューロコンピューティング研究会，201406，沖縄

42. 金田有紀，園田翔，日野英逸，村田昇，``複数粒子フィルタとモデル選択を用いた EEG データの電流ダイポール推定” 情報論的学習理論と機械学習研究会，201406，沖縄

41. 高野健，小林芽衣，日野英逸，村田昇，``マーク付き点過程間の距離計算手法と判別への応用” [2014年度IBISML研究会賞]，情報論的学習理論と機械学習研究会，201406，沖縄

40. 野村亮介，日野英逸，村田昇，吉田朋広，``機械学習による漸近展開の近似精度の予測”，2013年度統計関連学会連合大会, 201309, 大阪

39. 樋口翔，野田淳史，日野英逸，村田昇, ``スパイクデータ解析のためのグラフ構造モデリング”, ニューロコンピューティング研究会，201306，沖縄

38. 日野英逸, 藤木淳，赤穂昭太郎，望月義彦，村田昇, ``データ対の直線性に基づく画像上の類似度の定義 ~ 歪曲画像からの直線検出への応用 ~ ”, パターン認識・メディア理解研究会, 201306, 東京

37. 加藤利幸，日野英逸，村田昇, ``スパースコーディングを用いたマルチフレーム超解像”, コンピュータビジョンとイメージメディア研究会 (CVIM2013/5), 201305, 東京

36. 日野英逸，村田昇，``非線形判別の概観と応用”, Statistical Analysis and Related Topics: Theory, Methodology and Data Analysis (SART2012), 駒場，東京, 2012 年 12 月

35. 野田淳史，石田諒，日野英逸，龍野正実，赤穂昭太郎，村田昇，``ランダムウォークに基づいたグラフ構造モデリング”, 第91回数理モデル化と問題解決研究会 (MPS91), 京都, 2012 年 12 月

34. 日野英逸，越島健介，村田昇， ``カーネル層別逆回帰のためのモデル選択手法”，第91回数理モデル化と問題解決研究会 (MPS91), 京都, 2012 年 12 月

33. 日野英逸，Reyhani Nima，``線型判別分析のための教師付きスパース共分散推定”，第15回情報論的学習理論ワークショップ (IBIS2012) (情報論的学習理論と機械学習研究会)，東京，2012 年 11 月

32. 有竹俊光，日野英逸，村田昇，``スパースコーディングにおける基底生成のための単一母基底の学習”，第15 回情報論的学習理論ワークショップ (IBIS2012) (情報論的学習理論と機械学習研究会)，東京， 2012 年 11 月

31. 野村亮介，日野英逸，村田昇，吉田朋広，``漸近展開による近似精度の予測可能性”，第15回情報論的学習理論ワークショップ (IBIS2012) (情報論的学習理論と機械学習研究会)，東京，2012 年 11 月

30. 日野英逸，村田昇，``スパース表現の数理とその応用” (チュートリアル講演), コンピュータビジョンとイメージメディア研究会 (CVIM), 2012年9月

29. 沈浩洋, 日野英逸, 村田昇, ``クラスタリングによる家庭消費電力パターンの抽出”, 第86回数理モデル化と問題解決研究会 (MPS86), 東京, 2011年12月

28. 沈浩洋, 日野英逸, 村田昇, ``JIT モデリングによる太陽光発電量予測とその信頼性評価”, 第86回数理モデル化と問題解決研究会 (MPS86), 東京, 2011年12月

27. 日野英逸, 村田昇, ``ガウス性に基づく多重カーネル学習”[Honorable Mention], 第14回情報論的学習理論ワークショップ (IBIS2011) (情報論的学習理論と機械学習研究会)(Honorable Mention), 奈良, 2011 年 11 月

26. 寺園隆宏, 若尾真治, 沈浩洋, 日野英逸, 村田昇, ``Just-In-Time モデリングを用いた日射量予測における信頼度推定”, 電気学会新エネルギー・環境研究会, 北海道, 2011 年 11 月

25. 小川哲司, 日野英逸, 村田昇, 小林哲則, ``クラス内変動に頑健なカーネルマシンと話者照合への適用”, 日本音響学会 2011年秋季研究発表会 , 島根, 2011 年 9 月

24. 村田昇, 沈浩洋, 日野英逸, ``太陽光発電量予測とその信頼性評価”, 日本鉄鋼協会第 162 回秋季講演大会, 大阪, 2011年9月

23. 園田翔, 村田昇, 日野英逸, 進藤史裕, 北田宏, 加納学, ``ブートストラップフィルタによる溶鋼温度分布の予測と制御”, 日本鉄鋼協会第162回秋季講演大会, 大阪, 2011年9月

22. 藤木淳, 赤穂昭太郎, 日野英逸, 村田昇, ``較正画像における直線度の最大化に基づく放射対称歪曲の較正”, 第14 回画像の認識・理解シンポジウム(MIRU2011), 金沢, 2011年7月

21. 藤木淳, 赤穂昭太郎, 日野英逸, 村田昇, ``最適抽出可能性に基づく 1 次元低い超平面や超曲面のあてはめ ∼ ランダムサンプリングは大域的最適解の夢をみるか?∼” 第 14 回画像の認識・理解シンポジウム (MIRU2011), 金沢, 2011年7月

20. 小川哲司, 日野英逸, 村田昇, 小林哲則, ``条件付きエントロピー最小化基準に基づくマルチカーネル学習を用いた発話スタイル変動に頑健な話者照合”, 87回音声言語情報処理研究会(SIG-SLP), 北海道, 2011年7月

19. 藤木淳, 赤穂昭太郎, 日野英逸, 村田昇, ``ランダムサンプリングに基づく超曲面あてはめ”, パターン認識・メディア理解研究会 (PRMU), 名古屋, 2011年5月

古市茂, 日野英逸, ``2010 FIFA World Cup の数学的解析”, 環瀬戸内応用数理研究部会第14 回シンポジウム, 2011年 1 月

18. 古市茂, 日野英逸, ``ペロン‐フロベニウスの定理と重み付き関数に基づいたランキング法 –2010 FIFA World Cupを例に”, RIMS 研究集会: 独立性と従属性の数理—函数解析学の視点から, 京都, 2010年12月

17. 三浦和起, 日野英逸, 村田昇, ``クロスエントロピー最適化を用いた株価予測値の安定化手法”, 第 81 回数理モデル化と問題解決研究会 (MPS81), 福岡, 2010年12月

16. 小川哲司, 日野英逸, Nima Reyhani, 村田昇, 小林哲則, ``マルチカーネル学習を用いた話者認識における最適化の検討”, 第84回音声言語処理研究会 (SLP), 2010年12月

15. 藤木淳, 日野英逸, 赤穂昭太郎, ``較正画像における直線度に基づく放射対称歪曲の較正”, パターン認識・メディア理解研究会 (PRMU), 山口, 2010 年 12 月

14. 日野英逸,三浦和起,村田昇, ``分位点に基づく重み付きデータの情報量推定手法とその応用”[Honorable Mention], 第13回情報論的学習理論ワークショップ (IBIS2010) (情報論的学習理論と機械学習研究会)(Honorable Mention), 東京, 2010年11月

13. 小川哲司, 日野英逸, Nima Reyhani, 村田昇, 小林哲則, ``情報論的な最適化に基づくマルチカーネル学習を用いた話者認識”, 日本音響学会 2010 年秋季研究発表会, 大阪, 2010 年 9 月

12. 藤木淳, 宇佐見由美, 日野英逸, 赤穂昭太郎, 村田昇, ``放射対称歪曲の較正に基づく回転対称鏡面形状の推定”, 画像の認識・理解シンポジウム (MIRU2010/7) , 北海道, 2010 年 7 月

11. 藤木淳，日野英逸, 宇佐見由美, 赤穂昭太郎, 村田昇, ``極射影平面を利用した放射対称歪曲の較正”, パターン認識・メディア理解研究会 (PRMU2010/3),2010 年 3 月

10. 日野英逸, 村田昇, ``条件付きエントロピー最小化に基づく教師付き次元削減手法”, 第12回情報論的学習理論ワークショップ (IBIS2009), 福岡, 2009 年 10 月

9. 藤木淳, 日野英逸, 宇佐見由美, 赤穂昭太郎, 村田昇, ``歪曲関数のモデル選択を利用した放射対称歪曲の較正”, 画像の認識・理解シンポジウム (MIRU 2009), 2009 年 7 月

7. 藤木淳, 日野英逸, 村田昇, 赤穂昭太郎, ``頑健なヤコビ核主成分分析に向けて”, コンピュータビジョンとイメージメディア研究会 (CVIM), 2009 年 3 月

6. 藤木淳, 赤穂昭太郎, 日野英逸, 村田昇, ``主成分曲線のあてはめによる放射対称歪曲の較正”, パターン認識・メディア理解研究会 (PRMU), 2008 年 12 月

5. 日野英逸, 藤本悠, 村田昇, ``Grouped ranking モデル: Plackett-Luce モデルの一般化とその応用”, 第11回情報論的学習理論ワークショップ (IBIS2008), 宮城, 2008 年 10 月

4. 高橋健太, 日野英逸, 村上隆夫, ``生体情報の情報量に関する一考察”, コンピュータセキュリティ研究会 (情報処理学会)(CSEC71), 北海道, 2007 年 7 月

3. 日野英逸, 高橋健太, 磯部義明, ``入退室管理のための存在確率計算モデル”, 数理モデル化と問題解決研究会 (情報処理学会)(MPS61), 大阪, 2006 年 9 月

2. 上野嘉夫, 日野英逸, 石渡康恵, ``順序つきデータに対する量子探索アルゴリズムの幾何と力学 (1)“, 応用数理学会, 宮城, 2005 年 9 月

1. 上野嘉夫, 石渡康恵, 日野英逸, ``順序つきデータに対する量子探索アルゴリズムの幾何と力学 (2)“, 応用数理学会, 宮城, 2005 年 9 月

Book, Book Chapter

5. ``マテリアル・機械学習・ロボット（現代化学増刊48）'', 東京化学同人，2024/03/26（執筆分担：「ベイズ最適化の停止基準」）

4. "Progress in Information Geometry: Theory and Applications", Springer Nature, 2021, (Chapter 4, "Contact Hamiltonian Systems for Probability Distribution Functions and Expectation Variables: A Study Based on a Class of Master Equations", with Shin-itiro Goto)

3. "統計学実践ワークブック"，学術図書出版社，2020年5月（執筆分担）

2. “岩波データサイエンス Vol. 5”, 岩波書店，2017 年 2 月, (時間遷移のスパース性)

“コンピュータビジョン最先端ガイド 6”, アドコム・メディア，2013 年 12 月，(第3章「スパース表現の数理と応用」を執筆)

Preprint

40. Tam Le, Truyen Nguyen, Hideitsu Hino, Kenji Fukumizu, ``Generalized Sobolev IPM for Graph-Based Measures'', https://arxiv.org/abs/2510.25591

39. Hiroshi Tamano, Hideitsu Hino, Daichi Mochihashi, ``Misspecifying non-compensatory as compensatory IRT: analysis of estimated skills and variance'', https://arxiv.org/abs/2507.15222

38. Keishi Sando, Hideitsu Hino, ``Complex non-backtracking matrix for directed graphs'', https://arxiv.org/abs/2507.12503

37. Hideaki Ishibashi, Kota Matsui, Kentaro Kutsukake, Hideitsu Hino, ``An (ε,δ)-accurate level set estimation with a stopping criterion'', https://arxiv.org/abs/2503.20272

36. Tam Le, Truyen Nguyen, Hideitsu Hino, Kenji Fukumizu, ``Orlicz-Sobolev Transport for Unbalanced Measures on a Graph'', https://arxiv.org/abs/2502.00739

35. Tam Le, Truyen Nguyen, Hideitsu Hino, Kenji Fukumizu, ``Scalable Sobolev IPM for Probability Measures on a Graph'', https://arxiv.org/abs/2502.00737

34. Takahiro Kawashima, Hideitsu Hino, ``A Family of Distributions of Random Subsets for Controlling Positive and Negative Dependence'', https://arxiv.org/abs/2408.01022

33. Hideitsu Hino, Keisuke Yano, ``Duality induced by an embedding structure of determinantal point process''. http://arxiv.org/abs/2404.11024

32. Masanari Kimura, Hideitsu Hino, ``A Short Survey on Importance Weighting for Machine Learning'', https://arxiv.org/abs/2403.10175

31. Thong Pham, Shohei Shimizu, Hideitsu Hino, Tam Le, ``Scalable Counterfactual Distribution Estimation in Multivariate Causal Models'', https://arxiv.org/abs/2311.00927

30. Takeshi Kanda, Toshimitsu Aritake, Kaoru Ohyama, Kaspar E. Vogt, Yuichi Makino, Thomas J. McHugh, Hideitsu Hino, Shotara Akaho, Noboru Murata, ``Hawkes process modeling quantifies complicated firing behaviors of cortical neurons during sleep and wakefulness'', https://doi.org/10.1101/2023.07.29.550297

29. Masanari Kimura, Hideitsu Hino, ``Information Geometrically Generalized Covariate Shift Adaptation'', https://doi.org/10.48550/arXiv.2304.09387

28. Hideitsu Hino, Shinto Eguchi, ``Active learning by query by committee with robust divergences'', https://arxiv.org/abs/2211.10013

27. Toshimitsu Aritake, Hideitsu Hino, ``Unsupervised Domain Adaptation for Extra Features in the Target Domain Using Optimal Transport'', https://arxiv.org/abs/2209.04594

26. Takahiro Kawashima, Hideitsu Hino, ``Gaussian Process Koopman Mode Decomposition'', https://arxiv.org/abs/2209.04111

25. Hideitsu Hino, Shotaro Akaho, Noboru Murata, ``Geometry of EM and related iterative algorithms'', http://arxiv.org/abs/2209.01301

24. Shogo Sagawa, Hideitsu Hino, ``Gradual Domain Adaptation via Normalizing Flows'', https://arxiv.org/abs/2206.11492

23. Masanari Kimura, Hideitsu Hino, ``Information Geometry of Dropout Training'', https://arxiv.org/abs/2206.10936

22. Hajime Ono, Kazuhiro Minami, Hideitsu Hino, ``One-bit Submission for Locally Private Quasi-MLE: Its Asymptotic Normality and Limitation'', https://arxiv.org/abs/2202.07194

21. Shogo Sagawa, Hideitsu Hino, ``Cost-effective Framework for Gradual Domain Adaptation with Multifidelity'', https://arxiv.org/abs/2202.04359, code available from here

20. Shin-itiro Goto, Hideitsu Hino, "Fast symplectic integrator for Nesterov-type acceleration method", https://arxiv.org/abs/2106.07620, code available from here

19. Hideaki Ishibashi, Hideitsu Hino, "Stopping Criterion for Active Learning Based on Error Stability", http://arxiv.org/abs/2104.01836

18. Masanari Kimura, Hideitsu Hino, "α-Geodesical Skew Divergence", https://arxiv.org/abs/2103.17060

17. Hideitsu Hino, "Active Learning: Problem Settings and Recent Developments", https://arxiv.org/abs/2012.04225

16. Keishi Sando, Hideitsu Hino, "Modal Principal Component Analysis", https://arxiv.org/abs/2008.03400, code available from here

15. Hideaki Ishibashi, Hideitsu Hino, "Stopping criterion for active learning based on deterministic generalization bounds", arxiv:2005.07402

14. Toshimitsu Aritake, Hideitsu Hino, Shigeyuki Namiki, Daisuke Asanuma, Kenzo Hirose, Noboru Murata, "Fast and robust multiplane single molecule localization microscopy using deep neural network", arXiv:2001.01893

13. Shotaro Akaho, Hideitsu Hino, Noboru Murata, "On a convergence property of a geometrical algorithm for statistical manifolds", arXiv:1909.12644

12. Shin-itiro Goto, Hideitsu Hino, "Diffusion equations from master equations -- A discrete geometric approach --", arXiv:1908.04535

11. Shin-itiro Goto, Hideitsu Hino, "Expectation variables on a para-contact metric manifold exactly derived from master equations", arXiv:1905.05939

10. Takashi Wada, Hideitsu Hino, "Bayesian Optimization for Multi-objective Optimization and Multi-point Search", arXiv:1905.02370

9. Daigo Shoji, Rina Noguchi, Shizuka Otsuki, Hideitsu Hino, "Classification of volcanic ash particles using a convolutional neural network and probability", arXiv:1805.12353

8. Shin-Itiro Goto, Hideitsu Hino, "Information and contact geometric description of expectation variables exactly derived from master equations", arXiv:1805.10592

7. Kenta Ueki, Hideitsu Hino, Tatsu Kuwatani, Kenta Ueki, Hideitsu Hino, Tatsu Kuwatani, "Geochemical discrimination and characteristics of magmatic tectonic settings; a machine learning-based approach", arXiv:1712.09016/doi:10.1029/2017GC007401

6. Rina Noguchi, Hideitsu Hino, Nobuo Geshi, Shizuka Otsuki, Kei Kurita, "New classification method of volcanic ash samples using statistically determined grain types", arXiv:1712.05566

5. Taishi Iwasaki, Hideitsu Hino, Masami Tatsuno, Shotaro Akaho, Noboru Murata, "Estimation of neural connections from partially observed neural spikes", arXiv:1711.03303

4. Toshiyuki Kato, Hideitsu Hino, Noboru Murata, "Double Sparse Multi-Frame Image Super Resolution", arXiv:1512.00607

3. Toshiyuki Kato, Hideitsu Hino, Noboru Murata, "Sparse Coding Approach for Multi-Frame Image Super Resolution", arXiv:1402.3926

2. Nima Reyhani, Hideitsu Hino, Ricardo Vigario, "New Probabilistic Bounds on Eigenvalues and Eigenvectors of Random Kernel Matrices", arXiv:1202.3761

1. Yoshio Uwano, Hideitsu Hino, Yasue Ishiwatari, "Certain integrable system on a space associated with a quantum search algorithm", arXiv:nlin/0512004

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