Adaptive evolutional learning method of neural networks using genetic algorithms under dynamic environments. - Shinichi Oeda; Takumi Ichimura; Mutsuhiro Terauchi; Tetsuyuki Takahama; Yoshinori Isomichi (KES, 2000)

An adaptive evolutional neuro learning method using genetic search and extraction of rules from trained networks. - Takumi Ichimura; Shinichi Oeda; Katsumi Yoshida (CEC, 2001)

Biological immune system by evolutionary adaptive learning of neural networks. - Shinichi Oeda; Takumi Icmmura; Toshiyuki Yamashita (IEEE Congress on Evolutionary Computation, 2002)

A Classification Capability of Reflective Neural Networks in Medical Databases. - Takumi Ichimura; Shinichi Oeda; Machi Suka; Katsumi Yoshida (KES, 2003)

A Classification Method of Medical Database by Immune Multi-agent Neural Networks with Planar Lattice Architecture. - Takumi Ichimura; Shinichi Oeda; Toshiyuki Yamashita; Katsumi Yoshida (KES, 2003)

A Proposal of Immune Multi-agent Neural Networks and Its Application to Medical Diagnostic System for Hepatobiliary Disorders. - Shinichi Oeda; Takumi Ichimura; Toshiyuki Yamashita; Katsumi Yoshida (KES, 2003)

Immune Multi Agent Neural Network and Its Application to the Coronary Heart Disease Database. - Shinichi Oeda; Takumi Ichimura; Katsumi Yoshida (KES, 2004)

Comparison of Proportional Hazard Model and Neural Network Models in a real data set of intensive care unit patients. - Machi Suka; Shinichi Oeda; Takumi Ichimura; Katsumi Yoshida; Jun Takezawa (MedInfo, 2004)

A learning method of immune multi-agent neural networks. - Takumi Ichimura; Shinichi Oeda; Machi Suka; Katsumi Yoshida (Neural Comput. Appl., 2005)

Time Series Data Classification Using Recurrent Neural Network with Ensemble Learning. - Shinichi Oeda; Ikusaburo Kurimoto; Takumi Ichimura (KES (3), 2006)

Advantages and Disadvantages of Neural Networks for Predicting Clinical Outcomes. - Machi Suka; Shinichi Oeda; Takumi Ichimura; Katsumi Yoshida; Jun Takezawa (IMECS, 2007)

Extracting Time-evolving Latent Skills from Examination Time Series. - Shinichi Oeda; Kenji Yamanishi (EDM, 2013)

Extracting Latent Skills from Time Series of Asynchronous and Incomplete Examinations. - Shinichi Oeda; Yu Ito; Kenji Yamanishi (EDM, 2014)

Student Modeling Method Integrating Knowledge Tracing and IRT with Decay Effect. - Shinichi Oeda; Kouta Asai (EKM@EKAW, 2016)

Rank Selection for Non-negative Matrix Factorization with Normalized Maximum Likelihood Coding. - Yu Ito; Shinichi Oeda; Kenji Yamanishi (SDM, 2016)

Log-Data Clustering Analysis for Dropout Prediction in Beginner Programming Classes. - Shinichi Oeda; Genki Hashimoto (KES, 2017)

Development of a Check Sheet for Code-review towards Improvement of Skill Level of Novice Programmers. - Shinichi Oeda; Hajime Kosaku (KES, 2018)

Student Modeling Using Convex Factorization Machines. - Shinichi Oeda; Daiki Shimizu; Hikaru Yamashita (FSDM, 2019)

Visualization of Programming Skill Structure by Log-Data Analysis with Decision Tree. - Shinichi Oeda; Mutsumi Chieda (KES, 2019)

Verification of Usefulness of Student Modeling with Real Educational Data using Convex Factorization Machines. - Shinichi Oeda; Daiki Shimizu (KES, 2021)

Data Preprocessing with IRM for skill extraction using NMF. - Shinichi Oeda; Shunsuke Iizumi (KES, 2022)

Latent State Estimation Method for Students Using Knowledge Tracing Combining with IRT. - Shinichi Oeda; Toma Kakizaki (KES, 2022)

Student modeling considering learning behavior history with deep factorization machines. - Toma Kakizaki; Shinichi Oeda (KES, 2023)

A student modeling method combining Deep Learning and forgetting models with Knowledge Tracing. - Shinichi Oeda; Shunichi Hasegawa (KES, 2023)

Deep Learning-based Source Code Classification and Visualization of Decision Rationales. - Shinichi Oeda; Seiya Mitsumori (KES, 2024)