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Shin Ishii: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Takeshi Mori, Yutaka Nakamura, Masa-aki Sato, Shin Ishii
    Reinforcement Learning for CPG-Driven Biped Robot. [Citation Graph (0, 0)][DBLP]
    AAAI, 2004, pp:623-630 [Conf]
  2. Yoichiro Matsuno, Tatsuya Yamazaki, Shin Ishii
    A multi-agent reinforcement learning method for a partially-observable competitive game. [Citation Graph (0, 0)][DBLP]
    Agents, 2001, pp:39-40 [Conf]
  3. Shigeyuki Oba, Kikuya Kato, Shin Ishii
    Multi-Scale Clustering for Gene Expression Profiling Data. [Citation Graph (0, 0)][DBLP]
    BIBE, 2005, pp:210-217 [Conf]
  4. Wako Yoshida, Shin Ishii
    A model-based reinforcement learning: a computational model and an fMRI study. [Citation Graph (0, 0)][DBLP]
    ESANN, 2003, pp:313-318 [Conf]
  5. Hajime Fujita, Shin Ishii
    Model-based reinforcement learning for a multi-player card game with partial observability. [Citation Graph (0, 0)][DBLP]
    IAT, 2005, pp:467-470 [Conf]
  6. Ken-ichi Amemori, Shin Ishii
    Gaussian Process Approach to Stochastic Spiking Neurons with Reset. [Citation Graph (0, 0)][DBLP]
    ICANN, 2001, pp:361-368 [Conf]
  7. Ken-ichi Amemori, Shin Ishii
    Resonance of a Stochastic Spiking Neuron Mimicking the Hodgkin-Huxley Model. [Citation Graph (0, 0)][DBLP]
    ICANN, 2001, pp:1087-1094 [Conf]
  8. Hajime Fujita, Yutaka Nakamura, Shin Ishii
    Feature Extraction for Decision-Theoretic Planning in Partially Observable Environments. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2006, pp:820-829 [Conf]
  9. Yutaka Nakamura, Takeshi Mori, Shin Ishii
    An Off-Policy Natural Policy Gradient Method for a Partial Observable Markov Decision Process. [Citation Graph (0, 0)][DBLP]
    ICANN (2), 2005, pp:431-436 [Conf]
  10. Shigeyuki Oba, Shin Ishii
    Semi-supervised Significance Score of Differential Gene Expressions. [Citation Graph (0, 0)][DBLP]
    ICANN (2), 2006, pp:808-817 [Conf]
  11. Shigeyuki Oba, Masa-aki Sato, Shin Ishii
    On-Line Learning Methods for Gaussian Processes. [Citation Graph (0, 0)][DBLP]
    ICANN, 2001, pp:292-299 [Conf]
  12. Shigeyuki Oba, Masa-aki Sato, Shin Ishii
    Prior Hyperparameters in Bayesian PCA. [Citation Graph (0, 0)][DBLP]
    ICANN, 2003, pp:271-279 [Conf]
  13. Shigeyuki Oba, Masa-aki Sato, Ichiro Takemasa, Morito Monden, Ken-ichi Matsubara, Shin Ishii
    Missing Value Estimation Using Mixture of PCAs. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:492-497 [Conf]
  14. Masa-aki Sato, Yutaka Nakamura, Shin Ishii
    Reinforcement Learning for Biped Locomotion. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:777-782 [Conf]
  15. Junichiro Yoshimoto, Shin Ishii, Masa-aki Sato
    Hierarchical Model Selection for NGnet Based on Variational Bayes Inference. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:661-666 [Conf]
  16. Junichiro Yoshimoto, Shin Ishii, Masa-aki Sato
    System Identification Based on Online Variational Bayes Method and Its Application to Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    ICANN, 2003, pp:123-131 [Conf]
  17. Taku Yoshioka, Ryouko Morioka, Kazuo Kobayashi, Shigeyuki Oba, Naotake Ogasawara, Shin Ishii
    Clustering of Gene Expression Data by Mixture of PCA Models. [Citation Graph (0, 0)][DBLP]
    ICANN, 2002, pp:522-527 [Conf]
  18. Naoto Yukinawa, Shigeyuki Oba, Kikuya Kato, Shin Ishii
    Multi-class Pattern Classification Based on a Probabilistic Model of Combining Binary Classifiers. [Citation Graph (0, 0)][DBLP]
    ICANN (2), 2005, pp:337-342 [Conf]
  19. Yasuo Nagayuki, Shin Ishii, Kenji Doya
    Multi-Agent Reinforcement Learning: An Approach Based on the Other Agent's Internal Model. [Citation Graph (0, 0)][DBLP]
    ICMAS, 2000, pp:215-221 [Conf]
  20. Ken-ichi Amemori, Shin Ishii
    Self-Organizing Network Learning of Sub-Millisecond Temporal Coded Information. [Citation Graph (0, 0)][DBLP]
    ICONIP, 1998, pp:1285-1288 [Conf]
  21. Masa-aki Sato, Shin Ishii
    On-Line EM Algorithm for Mixture of Local Experts. [Citation Graph (0, 0)][DBLP]
    ICONIP, 1998, pp:1397-1401 [Conf]
  22. Taku Yoshioka, Shin Ishii, Minoru Ito
    Strategy Acquisition for the Game "Othello" Based on Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    ICONIP, 1998, pp:841-844 [Conf]
  23. Takashi Bando, Tomohiro Shibata, Kenji Doya, Shin Ishii
    Switching Particle Filters for Efficient Real-time Visual Tracking. [Citation Graph (0, 0)][DBLP]
    ICPR (2), 2004, pp:720-723 [Conf]
  24. Junichiro Yoshimoto, Shin Ishii, Masa-aki Sato
    On-Line EM Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    IJCNN (3), 2000, pp:163-168 [Conf]
  25. Masa-aki Sato, Shin Ishii
    Reinforcement Learning Based on On-Line EM Algorithm. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:1052-1058 [Conf]
  26. Yutaka Nakamura, Takeshi Mori, Shin Ishii
    Natural Policy Gradient Reinforcement Learning for a CPG Control of a Biped Robot. [Citation Graph (0, 0)][DBLP]
    PPSN, 2004, pp:972-981 [Conf]
  27. Shigeyuki Oba, Masa-aki Sato, Ichiro Takemasa, Morito Monden, Ken-ichi Matsubara, Shin Ishii
    A Bayesian missing value estimation method for gene expression profile data. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2003, v:19, n:16, pp:2088-2096 [Journal]
  28. Ken-ichi Amemori, Shin Ishii
    Self-organization of delay lines by spike-time-dependent learning. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2004, v:61, n:, pp:291-316 [Journal]
  29. Shin Ishii, Masa-aki Sato
    Doubly constrained network for combinatorial optimization. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2002, v:43, n:1-4, pp:239-257 [Journal]
  30. Wako Yoshida, Shin Ishii
    Model-based reinforcement learning: a computational model and an fMRI study. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2005, v:63, n:, pp:253-269 [Journal]
  31. Junichiro Hirayama, Junichiro Yoshimoto, Shin Ishii
    Balancing plasticity and stability of on-line learning based on hierarchical Bayesian adaptation of forgetting factors. [Citation Graph (0, 0)][DBLP]
    Neurocomputing, 2006, v:69, n:16-18, pp:1954-1961 [Journal]
  32. Shin Ishii, Hajime Fujita, Masaoki Mitsutake, Tatsuya Yamazaki, Jun Matsuda, Yoichiro Matsuno
    A Reinforcement Learning Scheme for a Partially-Observable Multi-Agent Game. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2005, v:59, n:1-2, pp:31-54 [Journal]
  33. Ken-ichi Amemori, Shin Ishii
    Gaussian Process Approach to Spiking Neurons for Inhomogeneous Poisson Inputs. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2001, v:13, n:12, pp:2763-2797 [Journal]
  34. Shin Ishii, Hirotaka Niitsuma
    -Opt Neural Approaches to Quadratic Assignment Problems. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:9, pp:2209-2225 [Journal]
  35. Shin-ichi Maeda, Wen-Jie Song, Shin Ishii
    Nonlinear and Noisy Extension of Independent Component Analysis: Theory and Its Application to a Pitch Sensation Model. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2005, v:17, n:1, pp:115-144 [Journal]
  36. Masa-aki Sato, Shin Ishii
    On-line EM Algorithm for the Normalized Gaussian Network. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2000, v:12, n:2, pp:407-432 [Journal]
  37. Junichiro Hirayama, Junichiro Yoshimoto, Shin Ishii
    Bayesian representation learning in the cortex regulated by acetylcholine. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2004, v:17, n:10, pp:1391-1400 [Journal]
  38. Shin Ishii, Masa-aki Sato
    Reconstruction of chaotic dynamics by on-line EM algorithm. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2001, v:14, n:9, pp:1239-1256 [Journal]
  39. Shin Ishii, Masa-aki Sato
    Chaotic Potts Spin Model for Combinatorial Optimization Problems. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1997, v:10, n:5, pp:941-963 [Journal]
  40. Shin Ishii, Masa-aki Sato
    Constrained neural approaches to quadratic assignment problems. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 1998, v:11, n:6, pp:1073-1082 [Journal]
  41. Shin Ishii, Wako Yoshida, Junichiro Yoshimoto
    Control of exploitation-exploration meta-parameter in reinforcement learning. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2002, v:15, n:4-6, pp:665-687 [Journal]
  42. Yuichi Sakumura, Shin Ishii
    Stochastic resonance with differential code in feedforward network with intra-layer random connections. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2006, v:19, n:4, pp:469-476 [Journal]
  43. Yasunobu Igarashi, Yuichi Sakumura, Shin Ishii
    The role of short-term depression in sustained neural activity in the prefrontal cortex: A simulation study. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2006, v:19, n:8, pp:1137-1152 [Journal]
  44. Kentarou Hitomi, Tomohiro Shibata, Yutaka Nakamura, Shin Ishii
    Reinforcement learning for quasi-passive dynamic walking of an unstable biped robot. [Citation Graph (0, 0)][DBLP]
    Robotics and Autonomous Systems, 2006, v:54, n:12, pp:982-988 [Journal]
  45. Takashi Bando, Tomohiro Shibata, Kenji Doya, Shin Ishii
    Switching particle filters for efficient visual tracking. [Citation Graph (0, 0)][DBLP]
    Robotics and Autonomous Systems, 2006, v:54, n:10, pp:873-884 [Journal]
  46. Yoichiro Matsuno, Tatsuya Yamazaki, Jun Matsuda, Shin Ishii
    A multiagent reinforcement learning method based on the model inference of the other agents. [Citation Graph (0, 0)][DBLP]
    Systems and Computers in Japan, 2002, v:33, n:12, pp:67-76 [Journal]
  47. Hirotaka Niitsuma, Shin Ishii, Minoru Ito
    Analog lambda-opt approach to quadratic assignment problem. [Citation Graph (0, 0)][DBLP]
    Systems and Computers in Japan, 2000, v:31, n:10, pp:1-9 [Journal]
  48. Shigeyuki Oba, Masa-aki Sato, Shin Ishii
    Variational Bayes method for Mixture of Principal Component Analyzers. [Citation Graph (0, 0)][DBLP]
    Systems and Computers in Japan, 2003, v:34, n:11, pp:55-66 [Journal]
  49. Junichiro Yoshimoto, Shin Ishii, Masa-aki Sato
    Application of reinforcement learning based on on-line EM algorithm to balancing of acrobot. [Citation Graph (0, 0)][DBLP]
    Systems and Computers in Japan, 2001, v:32, n:5, pp:12-20 [Journal]
  50. Yasunori Ishihara, Shin Ishii, Hiroyuki Seki, Minoru Ito
    Temporal Reasoning about Two Concurrent Sequences of Events. [Citation Graph (0, 0)][DBLP]
    SIAM J. Comput., 2004, v:34, n:2, pp:498-513 [Journal]
  51. Atsunori Kanemura, Shin-ichi Maeda, Shin Ishii
    Edge-Preserving Bayesian Image Superresolution Based on Compound Markov Random Fields. [Citation Graph (0, 0)][DBLP]
    ICANN (2), 2007, pp:611-620 [Conf]
  52. Yuki Taniguchi, Takeshi Mori, Shin Ishii
    Reinforcement Learning for Cooperative Actions in a Partially Observable Multi-agent System. [Citation Graph (0, 0)][DBLP]
    ICANN (1), 2007, pp:229-238 [Conf]
  53. Takashi Takenouchi, Shin Ishii
    Multiclass classification as a decoding problem. [Citation Graph (0, 0)][DBLP]
    FOCI, 2007, pp:470-475 [Conf]
  54. Satoshi Osaga, Junichiro Hirayama, Takashi Takenouchi, Shin Ishii
    A Probabilistic Model of MOSAIC. [Citation Graph (0, 0)][DBLP]
    FOCI, 2007, pp:41-46 [Conf]
  55. Yutaka Nakamura, Takeshi Mori, Masa-aki Sato, Shin Ishii
    Reinforcement learning for a biped robot based on a CPG-actor-critic method. [Citation Graph (0, 0)][DBLP]
    Neural Networks, 2007, v:20, n:6, pp:723-735 [Journal]

  56. Self-organized Reinforcement Learning Based on Policy Gradient in Nonstationary Environments. [Citation Graph (, )][DBLP]


  57. A Continuous Internal-State Controller for Partially Observable Markov Decision Processes. [Citation Graph (, )][DBLP]


  58. An Additive Reinforcement Learning. [Citation Graph (, )][DBLP]


  59. Hidden Markov Model for Human Decision Process in a Partially Observable Environment. [Citation Graph (, )][DBLP]


  60. Noise-Induced Collective Migration for Neural Crest Cells. [Citation Graph (, )][DBLP]


  61. Learning color image expansion filters. [Citation Graph (, )][DBLP]


  62. A semiparametric statistical approach to model-free policy evaluation. [Citation Graph (, )][DBLP]


  63. Visual Tracking Achieved by Adaptive Sampling from Hierarchical and Parallel Predictions. [Citation Graph (, )][DBLP]


  64. Optimization of Parametric Companding Function for an Efficient Coding. [Citation Graph (, )][DBLP]


  65. Bayesian Collaborative Predictors for General User Modeling Tasks. [Citation Graph (, )][DBLP]


  66. Quantitative Morphodynamic Analysis of Time-Lapse Imaging by Edge Evolution Tracking. [Citation Graph (, )][DBLP]


  67. Interpreting Dopamine Activities in Stochastic Reward Tasks. [Citation Graph (, )][DBLP]


  68. On the Synchrony of Morphological and Molecular Signaling Events in Cell Migration. [Citation Graph (, )][DBLP]


  69. Learning of Go Board State Evaluation Function by Artificial Neural Network. [Citation Graph (, )][DBLP]


  70. Robust Approximation in Decomposed Reinforcement Learning. [Citation Graph (, )][DBLP]


  71. A Closed-Form Estimator of Fully Visible Boltzmann Machines. [Citation Graph (, )][DBLP]


  72. Superresolution from Occluded Scenes. [Citation Graph (, )][DBLP]


  73. A probabilistic decoding approach to multi-class classification. [Citation Graph (, )][DBLP]


  74. Estimation of the Source-Filter Model Using Temporal Dynamics. [Citation Graph (, )][DBLP]


  75. Heterogeneous Component Analysis. [Citation Graph (, )][DBLP]


  76. Dynamic Exponential Family Matrix Factorization. [Citation Graph (, )][DBLP]


  77. Optimal Online Learning Procedures for Model-Free Policy Evaluation. [Citation Graph (, )][DBLP]


  78. Fast and Stable Learning of Quasi-Passive Dynamic Walking by an Unstable Biped Robot based on Off-Policy Natural Actor-Critic. [Citation Graph (, )][DBLP]


  79. Reinforcement learning for a snake-like robot controlled by a central pattern generator. [Citation Graph (, )][DBLP]


  80. Virtual Force/Tactile Sensors for Interactive Machines Using the User's Biological Signals. [Citation Graph (, )][DBLP]


  81. Semi-supervised discovery of differential genes. [Citation Graph (, )][DBLP]


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