Improvement of presenting interface by predicting the evaluation order to reduce the burden of human interactive EC operators. - Miho Ohsaki; Hideyuki Takagi (SMC, 1998)

An input method using discrete fitness values for interactive GA. - Miho Ohsaki; Hideyuki Takagi; Kimiko Ohya (J. Intell. Fuzzy Syst., 1998)

Evaluation of edge detection methods through psychological tests-is the detected edge really desirable for humans? - Miho Ohsaki; Takahiro Sugiyama; Hideaki Ohno (SMC, 2000)

Investigation of Rule Interestingness in Medical Data Mining. - Miho Ohsaki; Shinya Kitaguchi; Hideto Yokoi; Takahira Yamaguchi (Active Mining, 2003)

Sampling point extraction based on genetic algorithm and function approximation of a search space. - Miho Ohsaki; Yoshifumi Banno; Tomohiro Yoshikawa; Tsuyoshi Shinogi; Nobuharu Tsuruoka (CIRA, 2003)

Comparison between Objective Interestingness Measures and Real Human Interest in Medical Data Mining. - Miho Ohsaki; Yoshinori Sato; Shinya Kitaguchi; Hideto Yokoi; Takahira Yamaguchi (IEA/AIE, 2004)

Evaluation of Rule Interestingness Measures with a Clinical Dataset on Hepatitis. - Miho Ohsaki; Shinya Kitaguchi; Kazuya Okamoto; Hideto Yokoi; Takahira Yamaguchi (PKDD, 2004)

Evaluating a Rule Evaluation Support Method with Learning Models Based on Objective Rule Evaluation Indices - A Case Study with a Meningitis Data Mining Result. - Hidenao Abe; Miho Ohsaki; Shusaku Tsumoto; Takahira Yamaguchi (HIS, 2005)

A Rule Evaluation Support Method with Learning Models Based on Objective Rule Evaluation Indexes. - Hidenao Abe; Shusaku Tsumoto; Miho Ohsaki; Takahira Yamaguchi (ICDM, 2005)

Implementing an Integrated Time-Series Data Mining Environment Based on Temporal Pattern Extraction Methods: A Case Study of an Interferon Therapy Risk Mining for Chronic Hepatitis. - Hidenao Abe; Miho Ohsaki; Hideto Yokoi; Takahira Yamaguchi (JSAI Workshops, 2005)

Evaluating Learning Algorithms Composed by a Constructive Meta-Learning Scheme for a Rule Evaluation Support Method. - Hidenao Abe; Shusaku Tsumoto; Miho Ohsaki; Takahira Yamaguchi (ICDM Workshops, 2006)

Proposal of Medical KDD Support User Interface Utilizing Rule Interestingness Measures. - Miho Ohsaki; Hidenao Abe; Shusaku Tsumoto; Hideto Yokoi; Takahira Yamaguchi (ICDM Workshops, 2006)

Evaluating Learning Algorithms for a Rule Evaluation Support Method Based on Objective Rule Evaluation Indices. - Hidenao Abe; Shusaku Tsumoto; Miho Ohsaki; Takahira Yamaguchi (ISMIS, 2006)

Evaluating Model Construction Methods with Objective Rule Evaluation Indices to Support Human Experts. - Hidenao Abe; Shusaku Tsumoto; Miho Ohsaki; Takahira Yamaguchi (MDAI, 2006)

Evaluating a Rule Evaluation Support Method Based on Objective Rule Evaluation Indices. - Hidenao Abe; Shusaku Tsumoto; Miho Ohsaki; Takahira Yamaguchi (PAKDD, 2006)

Evaluating Learning Algorithms with Meta-learning Schemes for a Rule Evaluation Support Method Based on Objective Indices. - Hidenao Abe; Shusaku Tsumoto; Miho Ohsaki; Hideto Yokoi; Takahira Yamaguchi (PKAW, 2006)

Evaluating Learning Models for a Rule Evaluation Support Method Based on Objective Indices. - Hidenao Abe; Shusaku Tsumoto; Miho Ohsaki; Takahira Yamaguchi (RSCTC, 2006)

Developing a Rule Evaluation Support Method Based on Objective Indices. - Hidenao Abe; Shusaku Tsumoto; Miho Ohsaki; Takahira Yamaguchi (RSKT, 2006)

Evaluating Learning Algorithms to Construct Rule Evaluation Models Based on Objective Rule Evaluation Indices. - Hidenao Abe; Shusaku Tsumoto; Miho Ohsaki; Takahira Yamaguchi (IEEE ICCI, 2007)

Evaluating Accuracies of a Trading Rule Mining Method Based on Temporal Pattern Extraction. - Hidenao Abe; Satoru Hirabayashi; Miho Ohsaki; Takahira Yamaguchi (MCD, 2007)

Evaluation of Learning Costs of Rule Evaluation Models Based on Objective Indices to Predict Human Hypothesis Construction Phases. - Hidenao Abe; Shusaku Tsumoto; Miho Ohsaki; Hideto Yokoi; Takahira Yamaguchi (GrC, 2007)

Developing an Integrated Time-Series Data Mining Environment for Medical Data Mining. - Hidenao Abe; Hideto Yokoi; Miho Ohsaki; Takahira Yamaguchi (ICDM Workshops, 2007)

Evaluating a Constructive Meta-learning Algorithm for a Rule Evaluation Support Method Based on Objective Indices. - Hidenao Abe; Shusaku Tsumoto; Miho Ohsaki; Takahira Yamaguchi (KES (2), 2007)

Evaluating Learning Models with Transitions of Human Interests Based on Objective Rule Evaluation Indices. - Hidenao Abe; Hideto Yokoi; Shusaku Tsumoto; Miho Ohsaki; Takahira Yamaguchi (MedInfo, 2007)

Evaluating learning algorithms for a rule evaluation support method. - Hidenao Abe; Shusaku Tsumoto; Miho Ohsaki; Takahira Yamaguchi (SMC, 2007)

Evaluation of rule interestingness measures in medical knowledge discovery in databases. - Miho Ohsaki; Hidenao Abe; Shusaku Tsumoto; Hideto Yokoi; Takahira Yamaguchi (Artif. Intell. Medicine, 2007)

Evaluating Learning Algorithms to Support Human Rule - Evaluation Based on Objective Rule Evaluation Indices. - Hidenao Abe; Shusaku Tsumoto; Miho Ohsaki; Takahira Yamaguchi (Data Sci. J., 2007)

Numerical Time-Series Pattern Extraction Based on Irregular Piecewise Aggregate Approximation and Gradient Specification. - Miho Ohsaki; Hidenao Abe; Takahira Yamaguchi (New Gener. Comput., 2007)

Interactive Evolutionary Computation-Based Hearing Aid Fitting. - Hideyuki Takagi; Miho Ohsaki (IEEE Trans. Evol. Comput., 2007)

Finding Functional Groups of Objective Rule Evaluation Indices Using PCA. - Hidenao Abe; Shusaku Tsumoto; Miho Ohsaki; Takahira Yamaguchi (PAKM, 2008)

Evaluating Learning Algorithms to Support Human Rule Evaluation with Predicting Interestingness Based on Objective Rule Evaluation Indices. - Hidenao Abe; Shusaku Tsumoto; Miho Ohsaki; Takahira Yamaguchi (Communications and Discoveries from Multidisciplinary Data, 2008)

Improvement of interactive EC fitting based on substitute evaluation using sound volume preference. - Miho Ohsaki (FUZZ-IEEE, 2009)

Analysis of Subsequence Time-Series Clustering Based on Moving Average. - Miho Ohsaki; Masakazu Nakase; Shigeru Katagiri (ICDM, 2009)

Evaluating Learning Algorithms Composed by a Constructive Meta-learning Scheme for a Rule Evaluation Support Method. - Hidenao Abe; Shusaku Tsumoto; Miho Ohsaki; Takahira Yamaguchi (Mining Complex Data, 2009)

Minimum Error Classification with geometric margin control. - Hideyuki Watanabe; Shigeru Katagiri; Kouta Yamada; Erik McDermott; Atsushi Nakamura; Shinji Watanabe 001; Miho Ohsaki (ICASSP, 2010)

Improving a rule evaluation support method based on objective indices. - Hidenao Abe; Shusaku Tsumoto; Miho Ohsaki; Takahira Yamaguchi (Int. J. Adv. Intell. Paradigms, 2010)

Minimum classification error training with geometric margin enhancement for robust pattern recognition. - Hideyuki Watanabe; Shigeru Katagiri; Miho Ohsaki (MLSP, 2011)

Minimum classification error training with automatic setting of loss smoothness. - Hideyuki Watanabe; Jun'ichi Tokuno; Tsukasa Ohashi; Shigeru Katagiri; Miho Ohsaki (MLSP, 2011)

Increasing virtual samples through loss smoothness determination in large geometric margin minimum classification error training. - Tsukasa Ohashi; Hideyuki Watanabe; Jun'ichi Tokuno; Shigeru Katagiri; Miho Ohsaki; Shigeki Matsuda; Hideki Kashioka (ICASSP, 2012)

Application of kernel logistic regression to the prediction of liver fibrosis stages in chronic hepatitis C. - Kenji Matsuda; Miho Ohsaki; Shigeru Katagiri; Hideto Yokoi; Katsuhiko Takabayashi (SCIS&ISIS, 2012)

Robust and Efficient Pattern Classification using Large Geometric Margin Minimum Classification Error Training. - Hideyuki Watanabe; Tsukasa Ohashi; Shigeru Katagiri; Miho Ohsaki; Shigeki Matsuda; Hideki Kashioka (J. Signal Process. Syst., 2014)

Minimum Classification Error Training Incorporating Automatic Loss Smoothness Determination. - Hideyuki Watanabe; Jun'ichi Tokuno; Tsukasa Ohashi; Shigeru Katagiri; Miho Ohsaki; Shigeki Matsuda; Hideki Kashioka (J. Signal Process. Syst., 2014)

Formulation of the kernel logistic regression based on the confusion matrix. - Miho Ohsaki; Kenji Matsuda; Peng Wang; Shigeru Katagiri; Hideyuki Watanabe (CEC, 2015)

Compact kernel classifiers trained with minimum classification error criterion. - Ryoma Tani; Hideyuki Watanabe; Shigeru Katagiri; Miho Ohsaki (MLSP, 2017)

Confusion-Matrix-Based Kernel Logistic Regression for Imbalanced Data Classification. - Miho Ohsaki; Peng Wang; Kenji Matsuda; Shigeru Katagiri; Hideyuki Watanabe; Anca L. Ralescu (IEEE Trans. Knowl. Data Eng., 2017)

Discovery of Sets and Representatives of Variables in Co-nonlinear Relationships by Neural Network Regression and Group Lasso. - Miho Ohsaki; Hayato Sasaki; Naoya Kishimoto; Shigeru Katagiri; Patrick Hang Hui Then (BIBM, 2018)

Optimal Classifier Model Status Selection using Bayes boundary uncertainty. - David Ha; Emilie Delattre; Yuya Tomotoshi; Masahiro Senda; Hideyuki Watanabe; Shigeru Katagiri; Miho Ohsaki (MLSP, 2018)

Body Part Diagram Recognition in Medical Records: Application of the Histograms of Oriented Gradients and the Mahalanobis-Distance-Based Classifier. - Miho Ohsaki; Hayato Sasaki; Hiroharu Kawanaka; Shigeru Katagiri (SCIS&ISIS, 2018)

Optimal Classifier Parameter Status Selection Based on Bayes Boundary-ness for Multi-ProtoType and Multi-Layer Perceptron Classifiers. - Yuya Tomotoshi; David Ha; Emilie Delattre; Hideyuki Watanabe; Xugang Lu; Shigeru Katagiri; Miho Ohsaki (IUKM, 2019)

Maximum Bayes Boundary-Ness Training For Pattern Classification. - Masahiro Senda; David Ha; Hideyuki Watanabe; Shigeru Katagiri; Miho Ohsaki (SPML, 2019)

Minimum Classification Error Training with Speech Synthesis-Based Regularization for Speech Recognition. - Naoto Umezaki; Takumi Okubo; Hideyuki Watanabe; Shigeru Katagiri; Miho Ohsaki (SPML, 2019)

Genetic Algorithms Using Neural Network Regression and Group Lasso for Dynamic Selection of Crossover Operators. - Masaya Kato; Miho Ohsaki; Kei Ohnishi (SCIS/ISIS, 2020)

A Practical Method Based on Bayes Boundary-Ness for Optimal Classifier Parameter Status Selection. - David Ha; Yuya Tomotoshi; Masahiro Senda; Hideyuki Watanabe; Shigeru Katagiri; Miho Ohsaki (J. Signal Process. Syst., 2020)

Evaluation of the Neural-network-based Method to Discover Sets and Representatives of Nonlinearly Dependent Variables. - Miho Ohsaki; Hayato Sasaki; Naoya Kishimoto; Shigeru Katagiri; Kei Ohnishi; Yakub Sebastian; Patrick H. H. Then (CYBCONF, 2021)

NNR-GL: A Measure to Detect Co-Nonlinearity Based on Neural Network Regression Regularized by Group Lasso. - Miho Ohsaki; Naoya Kishimoto; Hayato Sasaki; Ryoji Ikeura; Shigeru Katagiri; Kei Ohnishi; Yakub Sebastian; Patrick H. H. Then (IEEE Access, 2021)

An Improved Boundary Uncertainty-Based Estimation for Classifier Evaluation. - David Ha; Shigeru Katagiri; Hideyuki Watanabe; Miho Ohsaki (J. Signal Process. Syst., 2021)

Experiment to Investigate Awareness of Tastes for Users in Interactive Evolutionary Computation. - Rina Obata; Kei Ohnishi; Makoto Fukumoto; Miho Ohsaki (SCIS/ISIS, 2022)

An Investigation of Feature Difference Between Child and Adult Voices Using Line Spectral Pairs. - Ginji Hayashi; Shigeru Katagiri; Xugang Lu; Miho Ohsaki (SPML, 2022)

A Proposal of an Improved Maximum Bayes Boundary-Ness Training Method. - Koki Kishishita; Shigeru Katagiri; Miho Ohsaki (SPML, 2022)

Domain Adaptation for Japanese Sentence Embeddings with Contrastive Learning based on Synthetic Sentence Generation. - Zihao Chen; Hisashi Handa; Miho Ohsaki; Kimiaki Shirahama (CoRR, 2025)