PUBLICATION

Journal Papers

    • "Bayesian inference for 3D helical reconstruction using soft-body model"
    • M. Ohashi, S. Maeda, and C. Sato.
    • Physical Review E, 100, 042411 (2019).
    • "Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning"
    • T. Miyato, S. Maeda, M. Koyama, and S. Ishii.
    • IEEE transactions on Pattern Analysis and Machine Intelligence, 41(8), 1979-1993, (2019).
    • "Constructing a Meta-Tracker using Dropout to Imitate the Behavior of an Arbitrary Black-box Tracker Learning Systems"
    • K. Meshgi, S. Maeda, S. Oba, and S. Ishii.
    • Neural Networks, 87, 132-148, (2017).
    • "Sparse Bayesian linear regression with latent masking variables"
    • Y. Kondo, K. Hayashi, and S. Maeda.
    • Neurocomputing, 258(4), 3-12, (2017).
    • "An Occlusion-Aware Particle Filter Tracker to Handle Complex and Persistent Occlusions using Multiple Feature Fusion"
    • K. Meshgi, S. Maeda, S. Oba, H. Skibbe, Y. Li, and S. Ishii.
    • Journal of Computer Vision and Image Understanding, 150, 81-94, (2016).
    • "Efficient Monte Carlo Image Analysis for the Location Of Vascular Entity"
    • H. Skibbe, M. Reisert, S. Maeda, M. Koyama, and S. Ishiii.
    • IEEE Transactions on medical imaging, 34(2), 628-643, (2014).
    • "状態非依存の方策を用いた新しい強化学習手法の提案"
    • 中野太智, 前田新一, 石井信.
    • システム制御情報学会論文誌, 27(8), 327-332, (2014).
    • "Low-dimensional Feature Representation for Instrument Identification"
    • M. Ihara, S. Maeda, K. Ikeda, and S. Ishii.
    • SICE Journal of Control, Measument, and System Integration, 5(4), 249-258, (2012).
    • "Asymptotic analysis of value prediction by well-specified and misspecified models"
    • T. Ueno, S. Maeda, and S. Ishii.
    • Neural Networks, 31, 88-92, (2012).
    • "Generalized TD Learning"
    • T. Ueno, S. Maeda, M. Kawanabe and S. Ishii.
    • Journal of Machine Learning Research, 12, 1977-2020, (2011).
    • "Semaphorin 3A induces Ca_v2.3 channel-dependent conversion of axons to dendrites"
    • M. Nishiyama, K. Togashi, M. J. von Schimmelmann, C. Lim, S. Maeda, N. Yamashita, Y. Goshima, S. Ishii and K. Hong .
    • Nature Cell Biology, 13(6), 676-685, (2011).
    • "Maximum a Posteriori X-ray Computed tomography using graph cuts"
    • S. Maeda, W. Fukuda, A. Kanemura, and S. Ishii.
    • Journal of Physics: Conference Series, 233, 012023, (2010). (doi:10.1088/1742-6596/233/1/012023)
    • "Sparse Bayesian Learning of Filters for Efficient Image Expansion"
    • A. Kanemura, S. Maeda, and S. Ishii.
    • IEEE Transactions on image processing, 19(6), 1480-1490, (2010).
    • "Bayesian Image Superresolution and Hidden Variable Modeling"
    • A. Kanemura, S. Maeda, W. Fukuda, and S. Ishii.
    • Journal of Systems Science and Complexity, 23(1), 116-136, (2010).
    • "Learning a multidimensional companding function for lossy source coding"
    • S. Maeda and S. Ishii.
    • Neural Networks, 22(7), 998-1010, (2009). (doi:10.1016/j.neunet.2009.06.001)
    • "複層マルコフ確率場を事前分布とする超解像法におけるハイパーパラメータ推定"
    • 兼村厚範, 前田新一, 石井信.
    • 電子情報通信学会論文誌(D), J92-D(10), 1802-1811, (2009). (doi:10.1016/j.neunet.2009.06.001)
    • "Superresolution with Compound Markov Random Fields via the Variational EM Algorithm"
    • A. Kanemura, S. Maeda, and S. Ishii.
    • Neural Networks, 22(7), 1025-1034, (2009). (doi:10.1016/j.neunet.2008.12.005)
    • "Solo instrumental music analysis using the source-filter model as a sound production model considering temporal dynamics."
    • M. Ihara, S. Maeda, and S. Ishii.
    • Neural Computing & Applications, 18(1), 3-14, (2009). (doi:10.1007/s00521-008-0201-7)
    • "Markov and semi-Markov switching of source appearances for non-stationary independent component analysis"
    • J. Hirayama, S. Maeda, and S. Ishii.
    • IEEE Transactions on Neural Networks, 18(5), 1326-1342, (2007).
    • "Cortical intrinsic circuits can support activity propagation through an isofrequency strip of the guinea pig primary auditory cortex"
    • W.-J. Song, H. Kawaguchi, S. Totoki, I. Inoue, T. Katura,S. Maeda, S. Inagaki, H. Shirasawa, and M. Nishimura.
    • Cerebral Cortex, 16(5), 718-729, (doi:10.1093/cercor/bhj018), August 17, (2005).
    • "Nonlinear and noisy extension of independent component analysis: theory and its application to a pitch sensation model"
    • S. Maeda, W.-J. Song, and S. Ishii.
    • Neural Computation, 17(1), 115-144, (2005).
    • "学習によるproduct codeの設計"
    • 前田新一, 石井信.
    • 電子情報通信学会論文誌(A), J87-A, 382-390, (2004).
    • "Separation of signal and noise from in vivo optical recording in Guinea pigs using independent component analysis"
    • S. Maeda, S. Inagaki, H. Kawaguchi, and W.-J. Song.
    • Neuroscience Letters. 302, 137-140, (2001).

International Conferences

    • "Reconnaissance for reinforcement learning with safety constraints."
    • S. Maeda, H. Watahiki, Y. Ouyang, S. Okada, M. Koayama, and P. Nagarajan.
    • Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), (to appear).
    • "Uncertainty-Aware Self-Supervised Target-Mass Grasping of Granular Foods."
    • K. Takahashi, W. Ko, A. Ummadisingu, and S. Maeda.
    • IEEE International Conference on Robotics and Automation (ICRA), (2021).
    • "MANGA: Method Agnostic Neural-policy Generalization and Adaptation."
    • H. Bharadhwaj, S. Yamaguchi, and S. Maeda.
    • IEEE International Conference on Robotics and Automation (ICRA), 2020, 3356-3362, doi: 10.1109/ICRA40945.2020.9197398. (2020).
    • "Safe Reinforcement Learning with Adversarial Threat Functions."
    • W. Chung, S. Maeda, and Y. Fujita.
    • NeurIPS2019 Workshop on Safety and Robustness in Decision Making, (2019).
    • "Exploring Unexplored Tensor Decompositions for Convolutional Neural Networks."
    • K. Hayashi, T. Yamaguchi, Y. Sugawara, and S. Maeda.
    • Thirty-third Conference on Neural Information Processing Systems, (2019).
    • "Robustness to Adversarial Perturbations in Learning from Incomplete Data."
    • A. Najafi, S. Maeda, M. Koyama, T. Miyato.
    • Thirty-third Conference on Neural Information Processing Systems, (2019).
    • "DQN-TAMER: Human-in-the-Loop Reinforcement Learning with Intractable Feedback."
    • R. Arakawa, S. Kobayashi, Y. Unno, Y. Tsuboi, and S. Maeda.
    • International Conference on Robot and Automation, Workshop on Human-Robot Teaming Beyond Human Operational Speeds, (2019).
    • "Neural Multi-scale Image Compression."
    • K. Nakanishi, S. Maeda, T. Miyato, and D. Okanohara.
    • Asian Conference on Computer Vision (ACCV), (2018).
    • "BayesGrad: Explaining Predictions of Graph Convolutional Networks."
    • H. Akita, K. Nakago, T. Komatsu, Y. Sugawara, S. Maeda, Y. Baba, and H. Kashima.
    • International Conference on Neural Information Processing (ICONIP), LNCS 11305, 81-92, (2018).
    • "Clipped Action Policy Gradient."
    • Y. Fujita and S. Maeda.
    • International Conference on Machine Learning (ICML), JMLR Workshop and Conference Proceedings, 80, 1592-1601, (2018).
    • "Semi-supervised Learning of Hierarchical Representations of Molecules Using Neural Message Passing."
    • H. Nguyen, S. Maeda, and K.Oono.
    • Neural Information Processing (NIPS) Workshop on Machine Learning for Molecules and Materials, (2017).
    • "Neural Sequence Model Training via α-divergence Minimization."
    • S. Koyamada, Y. Kikuchi, A. Kanemura, S. Maeda, and S. Ishii.
    • International Conference on Machine Learning (ICML) Workshop on Learning to Generate Natural Language, (2017).
    • "Synthetic Gradient Methods with Virtual Forward-Backward Networks."
    • T. Miyato, D. Okanohara, S. Maeda, and M. Koyama.
    • International Conference on Learning Representation (ICLR) Workshop track, (2017).
    • "Data-driven Probabilistic Occlusion Mask to Promote Visual Tracking"
    • K. Meshgi, S. Maeda, S. Oba, and S. Ishii.
    • Conference on Computer and Robot Vision (CRV), (2016).
    • "Distributional Smoothing with Virtual Adversarial Training"
    • T. Miyato, S. Maeda, M. Koyama, K. Nakae, and S. Ishii.
    • International Conference on Learning Representations (ICLR), (2016).
    • "Bayesian Masking: Sparse Bayesian Estimation with Weaker Shrinkage Bias"
    • Y. Kondo, K. Hayashi, and S. Maeda.
    • Asian Conference on Machine Learning (ACML), JMLR Workshop and Conference Proceedings, 45, 49–64, (2015).
    • "Rebuilding Factorized Information Criterion: Asymptotically Accurate Marginal Likelihood"
    • K. Hayashi, S. Maeda, and R. Fujimaki.
    • International Conference on Machine Learning (ICML), JMLR Workshop and Conference Proceedings, 37, 1358–1366, (2015).
    • "Control of a Free-Falling Cat by Policy-Based Reinforcement Learning"
    • D. Nakano, S. Maeda, and S. Ishii.
    • International Conference on Artificial Neural Networks (ICANN), Lecture Notes in Artificial Intelligence, 7553, 116-123, (2012).
    • "Motion compensated X-ray CT algorithm for moving objects"
    • T. Tanaka, S. Maeda, and S. Ishii.
    • International Conference on Machine Learning and Applications (ICMLA), 80-83, (2011).
    • "Bayesian X-ray computed tomography using material class knowledge"
    • W. Fukuda, S. Maeda, A. Kanemura, and S. Ishii.
    • International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2126-2129, (2010).
    • "X-ray computed tomography using material-class modeling by Markov random field minimization"
    • W. Fukuda, A. Kanemura, S. Maeda, and S. Ishii.
    • International symposium on Artificial Life and Robotics (AROB), 662-665, (2010).
    • "Machine learning approach to 9-dof arm robot control"
    • S. Nishioka, S. Maeda, and S. Ishii.
    • International symposium on Artificial Life and Robotics (AROB), 282-285, (2010).
    • "Superresolution from occluded scenes"
    • W. Fukuda, S. Maeda, and S. Ishii.
    • International Conference on Neural Information Processing (ICONIP), LNCS 5864, 19-27, (2009).
    • "Learning of Go board state evaluation function by artificial neural network"
    • H. Tomizawa, S. Maeda, and S. Ishii.
    • International Conference on Neural Information Processing (ICONIP), LNCS 5863, 598-605, (2009).
    • "Learning color image expansion filters"
    • A. Kanemura, S. Maeda, and S. Ishii.
    • IEEE International Conference on Image Processing (ICIP), 357-360, (2009).
    • "Optimal online learning procedures for model-free policy evaluation"
    • T. Ueno T, S. Maeda, M. Kawanabe, and S. Ishii.
    • Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), Lecture Notes in Artificial Intelligence, 5782, 473 - 488, (2009).
    • "Gaussian process regression for rendering music performance"
    • K. Teramura, H. Okuma, Y. Taniguchi, S. Makimoto, and S. Maeda.
    • International Conference on Music Perception and Cognition (ICMPC), 167-172, (2008).
    • "A semiparametric statistical approach to model-free policy evaluation"
    • T. Ueno, M. Kawanabe, T. Mori, S. Maeda, and S. Ishii.
    • International Conference on Machine Learning (ICML), 1072-1079, (2008).
    • "Instrument identification in monophonic music using spectral information"
    • M. Ihara, S. Maeda, and S. Ishii.
    • IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), 607-611, (2007).
    • "Image superresolution under spatially structured Noise"
    • A. Kanemura, S. Maeda, and S. Ishii.
    • IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), 279-284, (2007).
    • "Optimization of parametric companding function for an efficient coding"
    • S. Maeda and S. Ishii.
    • International Conference on Neural Information Processing (ICONIP), LNCS 4984, 713-722, (2007).
    • "Convergence analysis of the EM algorithm and Joint minimization of free energy"
    • S. Maeda and S. Ishii.
    • IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 318-323, (2007).
    • "Hyperparameter estimation in Bayesian image superresolution with a compound Markov random field prior"
    • A. Kanemura, S. Maeda, and S. Ishii.
    • IEEE International Workshop on Machine Learning for Signal Processing (MLSP), 181-186, (2007).
    • "Edge-preserving Bayesian image superresolution based on compound Markov Random Fields"
    • A. Kanemura, S. Maeda, and S. Ishii.
    • International Conference on Artificial Neural Networks (ICANN), LNCS 4669, 611-620, (2007).
    • "Estimation of the source-filter model using temporal dynamics"
    • M. Ihara, S. Maeda, and S. Ishii.
    • International Joint Conference on Neural Networks (IJCNN 2007), 1803, (2007).
    • "Estimation of source-filter model via acoustical feature extraction by GA-like algorithm"
    • M. Ihara, S. Maeda, and S. Ishii.
    • International Symposium on Artificial Life and Robotics (AROB 12th '07), GS12-4.
    • "Bayesian super-resolution with a smooth-gap model"
    • A. Kanemura, S. Maeda, and S. Ishii.
    • ECCV Workshop on Statistical Methods in Multi-Image and Video Processing, pp. 85-93, (2006).
    • "A Bayesian approach to blind source separation with variable number of sources"
    • J. Hirayama, S. Maeda, and S. Ishii.
    • International Symposium on Artificial Life and Robotics (AROB 11th '06), GS19-6, (2006).
    • "Bayesian noisy ICA for source switching environments"
    • J. Hirayama, S. Maeda, and S. Ishii.
    • IEEE Workshop on Statistical Signal Processing (SSP'05), 232, (2005).
    • "A noisy nonlinear independent component analysis"
    • S. Maeda and S. Ishii.
    • IEEE International Workshop on Machine Learning in Signal Processing, 173-182, (2004).
    • "Optimization of product code"
    • S. Maeda and S. Ishii.
    • WSEAS Transactions on Systems, 2(3), 473-476, (2004).
    • "An auditory system for efficient coding of natural sounds"
    • S. Maeda and S. Ishii.
    • International Joint Conference on Neural Networks, Honolulu, 23-28, (2002).

Book chapters and Translations

    • "Reinforcement Learning" in Ikeuchi K. (eds) "Computer Vision"
    • S. Maeda
    • Springer, Cham. (2021)
    • https://doi.org/10.1007/978-3-030-03243-2_859-1
    • "Algorithms for Reinforcement Learning" (translation into Japanese)
    • Csaba Szepesvári
    • KYORITSU PRINTING CO., LTD. (2017).
    • "速習 強化学習 -アルゴリズムと基礎理論-"
    • 小山田創哲 (訳者代表・編集), 前田新一, 小山雅典 (監訳), 共立出版 (2017).
    • "人工知能学事典新版"
    • Matching Pursuitの項担当
    • 人工知能学会 (編集), 共立出版 (2017).
    • "これからの強化学習"
    • 2.1節, 3.7節担当
    • 牧野貴樹, 澁谷長史, 白川真一 (編著), 森北出版 (2016).
    • "深層学習: Deep Learning"
    • 第I部, 3章担当
    • 人工知能学会 (監修), 神嶌敏弘 (編集), 近代科学社 (2015).
    • "The Elements of Statistical Learning - Data Mining, Inference and Prediction -" (translation into Japanese)
    • Trevor Hastie, Robert Tibshirani and Jerome Friedman.
    • KYORITSU PRINTING CO., LTD. (2014).
    • "統計的学習の基礎 - データマイニング・推論・予測 -", 14.5節-14.10節担当,
    • 杉山 将, 井手 剛, 神嶌 敏弘, 栗田 多喜夫, 前田 英作 (監訳), 共立出版 (2014).