Yuta Ishikawa

According to our database, Yuta Ishikawa authored at least 9 papers between 2006 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2022

Correlation Analysis of Features for Fusing in User Verification Using EEG Evoked by Ultrasound.

Isao Nakanishi, Yuta Ishikawa, Kotaro Mukai

Proceedings of the 2022 Tenth International Symposium on Computing and Networking, CANDAR 2022, 2022

2010

Multi-directional search from the primitive initial point for Gaussian mixture estimation using variational Bayes method.

Yuta Ishikawa, Ichiro Takeuchi, Ryohei Nakano

Neural Networks, 2010

Differentially Aberrant Region Detection in Array CGH Data Based on Nearest Neighbor Classification Performance.

Yuta Ishikawa, Ichiro Takeuchi

Inf. Media Technol., 2010

Detecting differentially aberrant genomic regions in multi-sample array CGH experiments using nearest-neighbor multivariate test.

Yuta Ishikawa, Ichiro Takeuchi

Proceedings of the International Joint Conference on Neural Networks, 2010

2009

Variational Bayes from the Primitive Initial Point for Gaussian Mixture Estimation.

Yuta Ishikawa, Ichiro Takeuchi, Ryohei Nakano

Proceedings of the Neural Information Processing, 16th International Conference, 2009

A Bayesian Graph Clustering Approach Using the Prior Based on Degree Distribution.

Naoyuki Harada, Yuta Ishikawa, Ichiro Takeuchi, Ryohei Nakano

Proceedings of the Neural Information Processing, 16th International Conference, 2009

2008

EM Algorithm with PIP Initialization and Temperature-Based Selection.

Yuta Ishikawa, Ryohei Nakano

Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2008

2007

Obtaining EM Initial Points by Using the Primitive Initial Point and Subsampling Strategy.

Yuta Ishikawa, Ryohei Nakano

Proceedings of the International Joint Conference on Neural Networks, 2007

2006

Landscape of a Likelihood Surface for a Gaussian Mixture and its use for the EM Algorithm.

Yuta Ishikawa, Ryohei Nakano

Proceedings of the International Joint Conference on Neural Networks, 2006