| 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 | | 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 | | 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 |
