| 2019 | ICPRAM | Mixture of Multilayer Perceptron Regressions. | Ryohei Nakano, Seiya Satoh |
| 2019 | ICPRAM | Faster RBF Network Learning Utilizing Singular Regions. | Seiya Satoh, Ryohei Nakano |
| 2018 | ICAISC | A New Method for Learning RBF Networks by Utilizing Singular Regions. | Seiya Satoh, Ryohei Nakano |
| 2017 | IJCCI | Performance of Complex-Valued Multilayer Perceptrons Largely Depends on Learning Methods. | Seiya Satoh, Ryohei Nakano |
| 2017 | ICPRAM | How New Information Criteria WAIC and WBIC Worked for MLP Model Selection. | Seiya Satoh, Ryohei Nakano |
| 2016 | IJCNN | How complex-valued multilayer perceptron can predict the behavior of deterministic chaos. | Seiya Satoh, Ryohei Nakano |
| 2015 | IJCCI | A Yet Faster Version of Complex-valued Multilayer Perceptron Learning using Singular Regions and Search Pruning. | Seiya Satoh, Ryohei Nakano |
| 2015 | IJCNN | Complex-valued multilayer perceptron learning using singular regions and search pruning. | Seiya Satoh, Ryohei Nakano |
| 2014 | IC3K | Emergent Induction of L-system Grammar from a String with Deletion-type Transmutation. | Ryohei Nakano |
| 2014 | ICANN | Complex-Valued Multilayer Perceptron Search Utilizing Singular Regions of Complex-Valued Parameter Space. | Seiya Satoh, Ryohei Nakano |
| 2014 | IJCCI | Singularity Stairs Following with Limited Numbers of Hidden Units. | Seiya Satoh, Ryohei Nakano |
| 2012 | ICANN | Complex-Valued Multilayer Perceptron Search Utilizing Eigen Vector Descent and Reducibility Mapping. | Shinya Suzumura, Ryohei Nakano |
| 2011 | IJCCI | Learning Method Utilizing Singular Region of Multilayer Perceptron. | Ryohei Nakano, Seiya Satoh, Takayuki Ohwaki |
| 2010 | IC3K | Number Theory-based Induction of Deterministic Context-free L-system Grammar. | Ryohei Nakano, Naoya Yamada |
| 2010 | ICANN | Nominally Conditioned Linear Regression. | Yusuke Tanahashi, Ryohei Nakano, Kazumi Saito |
| 2009 | ICANN | Bidirectional Clustering of MLP Weights for Finding Nominally Conditioned Polynomials. | Yusuke Tanahashi, Ryohei Nakano |
| 2009 | ICONIP | A Bayesian Graph Clustering Approach Using the Prior Based on Degree Distribution. | Naoyuki Harada, Yuta Ishikawa, Ichiro Takeuchi, Ryohei Nakano |
| 2009 | ICONIP | Variational Bayes from the Primitive Initial Point for Gaussian Mixture Estimation. | Yuta Ishikawa, Ichiro Takeuchi, Ryohei Nakano |
| 2008 | IJCNN | Optimizing Sparse Kernel Ridge Regression hyperparameters based on leave-one-out cross-validation. | Masayuki Karasuyama, Ryohei Nakano |
| 2008 | KES | EM Algorithm with PIP Initialization and Temperature-Based Selection. | Yuta Ishikawa, Ryohei Nakano |
| 2008 | KES | Reducing SVR Support Vectors by Using Backward Deletion. | Masayuki Karasuyama, Ichiro Takeuchi, Ryohei Nakano |
| 2008 | KES | Prediction of Information Diffusion Probabilities for Independent Cascade Model. | Kazumi Saito, Ryohei Nakano, Masahiro Kimura |
| 2007 | AAAI | Extracting Influential Nodes for Information Diffusion on a Social Network. | Masahiro Kimura, Kazumi Saito, Ryohei Nakano |
| 2007 | IJCNN | Obtaining EM Initial Points by Using the Primitive Initial Point and Subsampling Strategy. | Yuta Ishikawa, Ryohei Nakano |
| 2007 | IJCNN | Optimizing SVR Hyperparameters via Fast Cross-Validation using AOSVR. | Masayuki Karasuyama, Ryohei Nakano |
| 2007 | KES | Learning Evaluation Functions of Shogi Positions from Different Sets of Games. | Kosuke Inagaki, Ryohei Nakano |
| 2007 | KES | Prediction of Link Attachments by Estimating Probabilities of Information Propagation. | Kazumi Saito, Ryohei Nakano, Masahiro Kimura |
| 2007 | KES | Nominally Piecewise Multiple Regression Using a Four-Layer Perceptron. | Yusuke Tanahashi, Daisuke Kitakoshi, Ryohei Nakano |
| 2006 | IJCNN | Landscape of a Likelihood Surface for a Gaussian Mixture and its use for the EM Algorithm. | Yuta Ishikawa, Ryohei Nakano |
| 2006 | IJCNN | Revised Optimizer of SVR Hyperparameters Minimizing Cross-Validation Error. | Masayuki Karasuyama, Daisuke Kitakoshi, Ryohei Nakano |
| 2006 | KES | Improving Convergence Performance of PageRank Computation Based on Step-Length Calculation Approach. | Kazumi Saito, Ryohei Nakano |
| 2006 | KES | Finding Nominally Conditioned Multivariate Polynomials Using a Four-Layer Perceptron Having Shared Weights. | Yusuke Tanahashi, Kazumi Saito, Daisuke Kitakoshi, Ryohei Nakano |
| 2005 | IJCNN | Yet faster method to optimize SVR hyperparameters based on minimizing cross-validation error. | Kenji Kobayashi, Daisuke Kitakoshi, Ryohei Nakano |
| 2005 | IJCNN | Weight sharing on naive Bayes document model. | Kazumi Saito, Ryohei Nakano |
| 2005 | IJCNN | Finding a succinct multi-layer perceptron having shared weights. | Yusuke Tanahashi, Xiang-Fang Chin, Kazumi Saito, Ryohei Nakano |
| 2005 | KES | Analysis for Adaptability of Policy-Improving System with a Mixture Model of Bayesian Networks to Dynamic Environments. | Daisuke Kitakoshi, Hiroyuki Shioya, Ryohei Nakano |
| 2005 | KES | Model Selection and Weight Sharing of Multi-layer Perceptrons. | Yusuke Tanahashi, Kazumi Saito, Ryohei Nakano |
| 2004 | IJCNN | Threshold-based multi-thread EM algorithm. | Tetsuro Kawai, Ryohei Nakano |
| 2004 | IJCNN | Extracting characteristic words of text using neural networks. | Kazumi Saito, Ryohei Nakano |
| 2004 | KES | Piecewise Multivariate Polynomials Using a Four-Layer Perceptron. | Yusuke Tanahashi, Kazumi Saito, Ryohei Nakano |
| 2004 | KES | Learning an Evaluation Function for Shogi from Data of Games. | Satoshi Tanimoto, Ryohei Nakano |
| 2003 | IJCNN | Optimizing Support Vector regression hyperparameters based on cross-validation. | Kentaro Ito, Ryohei Nakano |
| 2003 | IJCNN | Threshold-based dynamic annealing for multi-thread DAEM and its extreme. | Masaharu Takada, Ryohei Nakano |
| 2002 | DIS | Structuring Neural Networks through Bidirectional Clustering of Weights. | Kazumi Saito, Ryohei Nakano |
| 2001 | IDA | Finding Polynomials to Fit Multivariate Data Having Numeric and Nominal Variables. | Ryohei Nakano, Kazumi Saito |
| 2000 | DIS | Discovery of Nominally Conditioned Polynomials Using Neural Networks, Vector Quantizers and Decision Trees. | Kazumi Saito, Ryohei Nakano |
| 2000 | PAKDD | Discovery of Relevant Weights by Minimizing Cross-Validation Error. | Kazumi Saito, Ryohei Nakano |
| 1999 | DIS | Discovery of a Set of Nominally Conditioned Polynomials. | Ryohei Nakano, Kazumi Saito |
| 1998 | DIS | Computational Characteristics of Law Discovery Using Neural Networks. | Ryohei Nakano, Kazumi Saito |
| 1997 | ICANN | Unique Representations of Dynamical Systems Produced by Recurrent Neural Networks. | Masahiro Kimura, Ryohei Nakano |
| 1997 | ICONIP | Adaptive β Scheduling Learning Method of Finite State Automata by Recurrent Neural Networks. | Kenichi Arai, Ryohei Nakano |
| 1997 | ICONIP | Numeric Law Discovery Using Neural Networks. | Kazumi Saito, Ryohei Nakano |
| 1997 | IJCAI | Law Discovery using Neural Networks. | Kazumi Saito, Ryohei Nakano |
| 1996 | ICANN | Annealed RNN Learning of Finite State Automata. | Ken-ichi Arai, Ryohei Nakano |
| 1996 | ICANN | Learning Dynamical Systems Produced by Recurrent Neural Networks. | Masahiro Kimura, Ryohei Nakano |
| 1996 | PPSN | Scheduling by Genetic Local Search with Multi-Step Crossover. | Takeshi Yamada, Ryohei Nakano |
| 1994 | PPSN | Optimal Population Size under Constant Computation Cost. | Ryohei Nakano, Yuval Davidor, Takeshi Yamada |
| 1992 | PPSN | A Genetic Algorithm Applicable to Large-Scale Job-Shop Problems. | Takeshi Yamada, Ryohei Nakano |
| 1983 | ER | Integrity Checking in a Logic-Oriented ER Model. | Ryohei Nakano |