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* | 2009 | |
---|---|---|

58 | EE | Yusuke Tanahashi, Ryohei Nakano: Bidirectional Clustering of MLP Weights for Finding Nominally Conditioned Polynomials. ICANN (2) 2009: 155-164 |

2008 | ||

57 | EE | Masayuki Karasuyama, Ryohei Nakano: Optimizing Sparse Kernel Ridge Regression hyperparameters based on leave-one-out cross-validation. IJCNN 2008: 3463-3468 |

56 | EE | Yuta Ishikawa, Ryohei Nakano: EM Algorithm with PIP Initialization and Temperature-Based Selection. KES (3) 2008: 58-66 |

55 | EE | Kazumi Saito, Ryohei Nakano, Masahiro Kimura: Prediction of Information Diffusion Probabilities for Independent Cascade Model. KES (3) 2008: 67-75 |

54 | EE | Masayuki Karasuyama, Ichiro Takeuchi, Ryohei Nakano: Reducing SVR Support Vectors by Using Backward Deletion. KES (3) 2008: 76-83 |

2007 | ||

53 | Masahiro Kimura, Kazumi Saito, Ryohei Nakano: Extracting Influential Nodes for Information Diffusion on a Social Network. AAAI 2007: 1371-1376 | |

52 | EE | Yuta Ishikawa, Ryohei Nakano: Obtaining EM Initial Points by Using the Primitive Initial Point and Subsampling Strategy. IJCNN 2007: 1115-1120 |

51 | EE | Masayuki Karasuyama, Ryohei Nakano: Optimizing SVR Hyperparameters via Fast Cross-Validation using AOSVR. IJCNN 2007: 1186-1191 |

50 | Ying Yan, Yusuke Tanahashi, Ryohei Nakano: A Set of Linear Regressions with Automatic Nominal Space Partition Using a Four-Layer Perceptron. IMECS 2007: 53-58 | |

49 | EE | Kosuke Inagaki, Ryohei Nakano: Learning Evaluation Functions of Shogi Positions from Different Sets of Games. KES (3) 2007: 210-217 |

48 | EE | Yusuke Tanahashi, Daisuke Kitakoshi, Ryohei Nakano: Nominally Piecewise Multiple Regression Using a Four-Layer Perceptron. KES (3) 2007: 218-226 |

47 | EE | Kazumi Saito, Ryohei Nakano, Masahiro Kimura: Prediction of Link Attachments by Estimating Probabilities of Information Propagation. KES (3) 2007: 235-242 |

46 | EE | Kazumi Saito, Ryohei Nakano: Bidirectional clustering of weights for neural networks with common weights. Systems and Computers in Japan 38(10): 46-57 (2007) |

2006 | ||

45 | EE | Y. Ishikawa, Ryohei Nakano: Landscape of a Likelihood Surface for a Gaussian Mixture and its use for the EM Algorithm. IJCNN 2006: 1434-1440 |

44 | EE | Masayuki Karasuyama, Daisuke Kitakoshi, Ryohei Nakano: Revised Optimizer of SVR Hyperparameters Minimizing Cross-Validation Error. IJCNN 2006: 319-326 |

43 | EE | Kazumi Saito, Ryohei Nakano: Improving Convergence Performance of PageRank Computation Based on Step-Length Calculation Approach. KES (2) 2006: 945-952 |

42 | EE | Yusuke Tanahashi, Kazumi Saito, Daisuke Kitakoshi, Ryohei Nakano: Finding Nominally Conditioned Multivariate Polynomials Using a Four-Layer Perceptron Having Shared Weights. KES (2) 2006: 969-976 |

2005 | ||

41 | EE | Yusuke Tanahashi, Kazumi Saito, Ryohei Nakano: Model Selection and Weight Sharing of Multi-layer Perceptrons. KES (4) 2005: 716-722 |

40 | EE | Daisuke Kitakoshi, Hiroyuki Shioya, Ryohei Nakano: Analysis for Adaptability of Policy-Improving System with a Mixture Model of Bayesian Networks to Dynamic Environments. KES (4) 2005: 730-737 |

2004 | ||

39 | EE | Yusuke Tanahashi, Kazumi Saito, Ryohei Nakano: Piecewise Multivariate Polynomials Using a Four-Layer Perceptron. KES 2004: 602-608 |

38 | EE | Satoshi Tanimoto, Ryohei Nakano: Learning an Evaluation Function for Shogi from Data of Games. KES 2004: 609-615 |

2002 | ||

37 | EE | Kazumi Saito, Ryohei Nakano: Structuring Neural Networks through Bidirectional Clustering of Weights. Discovery Science 2002: 206-219 |

36 | EE | Ryohei Nakano, Kazumi Saito: Discovering Polynomials to Fit Multivariate Data Having Numeric and Nominal Variables. Progress in Discovery Science 2002: 482-493 |

35 | EE | Kazumi Saito, Ryohei Nakano: Extracting regression rules from neural networks. Neural Networks 15(10): 1279-1288 (2002) |

2001 | ||

34 | EE | Ryohei Nakano, Kazumi Saito: Finding Polynomials to Fit Multivariate Data Having Numeric and Nominal Variables. IDA 2001: 258-267 |

2000 | ||

33 | EE | Kazumi Saito, Ryohei Nakano: Discovery of Nominally Conditioned Polynomials Using Neural Networks, Vector Quantizers and Decision Trees. Discovery Science 2000: 325-329 |

32 | Kazumi Saito, Ryohei Nakano: Discovery of Relevant Weights by Minimizing Cross-Validation Error. PAKDD 2000: 372-375 | |

31 | Kazumi Saito, Ryohei Nakano: Second-Order Learning Algorithm with Squared Penalty Term. Neural Computation 12(3): 709-729 (2000) | |

30 | Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton: SMEM Algorithm for Mixture Models. Neural Computation 12(9): 2109-2128 (2000) | |

29 | EE | Ken-ichi Arai, Ryohei Nakano: Stable behavior in a recurrent neural network for a finite state machine. Neural Networks 13(6): 667-680 (2000) |

28 | EE | Masahiro Kimura, Ryohei Nakano: Dynamical systems produced by recurrent neural networks. Systems and Computers in Japan 31(4): 77-86 (2000) |

27 | EE | Naonori Ueda, Ryohei Nakano: EM algorithm with split and merge operations for mixture models. Systems and Computers in Japan 31(5): 1-11 (2000) |

26 | EE | Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton: Split and Merge EM Algorithm for Improving Gaussian Mixture Density Estimates. VLSI Signal Processing 26(1-2): 133-140 (2000) |

1999 | ||

25 | EE | Ryohei Nakano, Kazumi Saito: Discovery of a Set of Nominally Conditioned Polynomials. Discovery Science 1999: 287-298 |

1998 | ||

24 | EE | Ryohei Nakano, Kazumi Saito: Computational Characteristics of Law Discovery Using Neural Networks. Discovery Science 1998: 342-351 |

23 | EE | Naonori Ueda, Ryohei Nakano, Zoubin Ghahramani, Geoffrey E. Hinton: SMEM Algorithm for Mixture Models. NIPS 1998: 599-605 |

22 | EE | Takeshi Yamada, Kazuyuki Yoshimura, Ryohei Nakano: Information Operator Scheduling by Genetic Algorithms. SEAL 1998: 50-57 |

21 | EE | Naonori Ueda, Ryohei Nakano: Deterministic annealing EM algorithm. Neural Networks 11(2): 271-282 (1998) |

20 | EE | Masahiro Kimura, Ryohei Nakano: Learning dynamical systems by recurrent neural networks from orbits. Neural Networks 11(9): 1589-1599 (1998) |

1997 | ||

19 | Masahiro Kimura, Ryohei Nakano: Unique Representations of Dynamical Systems Produced by Recurrent Neural Networks. ICANN 1997: 403-408 | |

18 | Kazumi Saito, Ryohei Nakano: Law Discovery using Neural Networks. IJCAI 1997: 1078-1083 | |

17 | EE | Kazumi Saito, Ryohei Nakano: Partial BFGS Update and Efficient Step-Length Calculation for Three-Layer Neural Networks. Neural Computation 9(1): 123-141 (1997) |

1996 | ||

16 | Masahiro Kimura, Ryohei Nakano: Learning Dynamical Systems Produced by Recurrent Neural Networks. ICANN 1996: 133-138 | |

15 | Ken-ichi Arai, Ryohei Nakano: Annealed RNN Learning of Finite State Automata. ICANN 1996: 519-524 | |

14 | EE | Kazumi Saito, Ryohei Nakano: Second-order Learning Algorithm with Squared Penalty Term. NIPS 1996: 627-633 |

13 | EE | Takeshi Yamada, Ryohei Nakano: Scheduling by Genetic Local Search with Multi-Step Crossover. PPSN 1996: 960-969 |

1995 | ||

12 | Kazumi Saito, Ryohei Nakano: A Connectionist Approach to Numeric Law Discorvery. Machine Intelligence 15 1995: 315-327 | |

1994 | ||

11 | Kazumi Saito, Ryohei Nakano: Adaptive Concept Learning Algorithm. IFIP Congress (1) 1994: 294-299 | |

10 | EE | Naonori Ueda, Ryohei Nakano: Deterministic Annealing Variant of the EM Algorithm. NIPS 1994: 545-552 |

9 | EE | Ryohei Nakano, Yuval Davidor, Takeshi Yamada: Optimal Population Size under Constant Computation Cost. PPSN 1994: 130-138 |

8 | EE | Naonori Ueda, Ryohei Nakano: A new competitive learning approach based on an equidistortion principle for designing optimal vector quantizers. Neural Networks 7(8): 1211-1227 (1994) |

1993 | ||

7 | Yuval Davidor, Takeshi Yamada, Ryohei Nakano: The ECOlogical Framework II : Improving GA Performance At Virtually Zero Cost. ICGA 1993: 171-176 | |

6 | Kazumi Saito, Ryohei Nakano: A concept learning algorithm with adaptive search. Machine Intelligence 14 1993: 353- | |

1992 | ||

5 | Takeshi Yamada, Ryohei Nakano: A Genetic Algorithm Applicable to Large-Scale Job-Shop Problems. PPSN 1992: 283-292 | |

1991 | ||

4 | Ryohei Nakano, Takeshi Yamada: Conventional Genetic Algorithm for Job Shop Problems. ICGA 1991: 474-479 | |

1990 | ||

3 | EE | Ryohei Nakano: Translation with Optimization from Relational Calculus to Relational Algebra Having Aggregate Functions. ACM Trans. Database Syst. 15(4): 518-557 (1990) |

1987 | ||

2 | Ryohei Nakano, Minoru Kiyama: MACH: Much Faster Associative Machine. IWDM 1987: 339-352 | |

1983 | ||

1 | EE | Ryohei Nakano: Integrity Checking in a Logic-Oriented ER Model. ER 1983: 551-564 |

1 | Ken-ichi Arai | [15] [29] |

2 | Yuval Davidor | [7] [9] |

3 | Zoubin Ghahramani | [23] [26] [30] |

4 | Geoffrey E. Hinton | [23] [26] [30] |

5 | Kosuke Inagaki | [49] |

6 | Y. Ishikawa | [45] |

7 | Yuta Ishikawa | [52] [56] |

8 | Masayuki Karasuyama | [44] [51] [54] [57] |

9 | Masahiro Kimura | [16] [19] [20] [28] [47] [53] [55] |

10 | Daisuke Kitakoshi | [40] [42] [44] [48] |

11 | Minoru Kiyama | [2] |

12 | Kazumi Saito | [6] [11] [12] [14] [17] [18] [24] [25] [31] [32] [33] [34] [35] [36] [37] [39] [41] [42] [43] [46] [47] [53] [55] |

13 | Hiroyuki Shioya | [40] |

14 | Ichiro Takeuchi | [54] |

15 | Yusuke Tanahashi | [39] [41] [42] [48] [50] [58] |

16 | Satoshi Tanimoto | [38] |

17 | Naonori Ueda | [8] [10] [21] [23] [26] [27] [30] |

18 | Takeshi Yamada | [4] [5] [7] [9] [13] [22] |

19 | Ying Yan | [50] |

20 | Kazuyuki Yoshimura | [22] |