Miho Ohsaki

62 papers A* 2B 7C 4Misc 3Journal 14Unranked 30
YearRankTypeTitle / Venue / Authors
2025 J jnl
Domain Adaptation for Japanese Sentence Embeddings with Contrastive Learning based on Synthetic Sentence Generation.
CoRR
Zihao Chen, Hisashi Handa, Miho Ohsaki, Kimiaki Shirahama
2025 J jnl
Feature Space Analysis by Guided Diffusion Model.
CoRR
Kimiaki Shirahama, Miki Yanobu, Kaduki Yamashita, Miho Ohsaki
2024 — conf
Doshisha University, Universität zu Lübeck and German Research Center for Artificial Intelligence at TRECVID 2024: QFISC Task.
TREC
Zihao Chen, Falco Lentzsch, Nele Sophie Brügge, Frédéric Li, Miho Ohsaki, Heinz Handels, Marcin Grzegorzek, Kimiaki Shirahama
2022 — conf
A Proposal of an Improved Maximum Bayes Boundary-Ness Training Method.
SPML
Koki Kishishita, Shigeru Katagiri, Miho Ohsaki
2022 — conf
An Investigation of Feature Difference Between Child and Adult Voices Using Line Spectral Pairs.
SPML
Ginji Hayashi, Shigeru Katagiri, Xugang Lu, Miho Ohsaki
2022 — conf
Experiment to Investigate Awareness of Tastes for Users in Interactive Evolutionary Computation.
SCIS/ISIS
Rina Obata, Kei Ohnishi, Makoto Fukumoto, Miho Ohsaki
2021 J jnl
An Improved Boundary Uncertainty-Based Estimation for Classifier Evaluation.
J. Signal Process. Syst.
David Ha, Shigeru Katagiri, Hideyuki Watanabe, Miho Ohsaki
2021 — conf
Evaluation of the Neural-network-based Method to Discover Sets and Representatives of Nonlinearly Dependent Variables.
CYBCONF
Miho Ohsaki, Hayato Sasaki, Naoya Kishimoto, Shigeru Katagiri, Kei Ohnishi, Yakub Sebastian, Patrick H. H. Then
2021 J jnl
NNR-GL: A Measure to Detect Co-Nonlinearity Based on Neural Network Regression Regularized by Group Lasso.
IEEE Access
Miho Ohsaki, Naoya Kishimoto, Hayato Sasaki, Ryoji Ikeura, Shigeru Katagiri, Kei Ohnishi, Yakub Sebastian, Patrick H. H. Then
2020 J jnl
A Practical Method Based on Bayes Boundary-Ness for Optimal Classifier Parameter Status Selection.
J. Signal Process. Syst.
David Ha, Yuya Tomotoshi, Masahiro Senda, Hideyuki Watanabe, Shigeru Katagiri, Miho Ohsaki
2020 — conf
Genetic Algorithms Using Neural Network Regression and Group Lasso for Dynamic Selection of Crossover Operators.
SCIS/ISIS
Masaya Kato, Miho Ohsaki, Kei Ohnishi
2019 — conf
Maximum Bayes Boundary-Ness Training For Pattern Classification.
SPML
Masahiro Senda, David Ha, Hideyuki Watanabe, Shigeru Katagiri, Miho Ohsaki
2019 — conf
Minimum Classification Error Training with Speech Synthesis-Based Regularization for Speech Recognition.
SPML
Naoto Umezaki, Takumi Okubo, Hideyuki Watanabe, Shigeru Katagiri, Miho Ohsaki
2019 — conf
Optimal Classifier Parameter Status Selection Based on Bayes Boundary-ness for Multi-ProtoType and Multi-Layer Perceptron Classifiers.
IUKM
Yuya Tomotoshi, David Ha, Emilie Delattre, Hideyuki Watanabe, Xugang Lu, Shigeru Katagiri, Miho Ohsaki
2018 — conf
Body Part Diagram Recognition in Medical Records: Application of the Histograms of Oriented Gradients and the Mahalanobis-Distance-Based Classifier.
SCIS&ISIS
Miho Ohsaki, Hayato Sasaki, Hiroharu Kawanaka, Shigeru Katagiri
2018 — conf
Discovery of Sets and Representatives of Variables in Co-nonlinear Relationships by Neural Network Regression and Group Lasso.
BIBM
Miho Ohsaki, Hayato Sasaki, Naoya Kishimoto, Shigeru Katagiri, Patrick Hang Hui Then
2018 — conf
Optimal Classifier Model Status Selection using Bayes boundary uncertainty.
MLSP
David Ha, Emilie Delattre, Yuya Tomotoshi, Masahiro Senda, Hideyuki Watanabe, Shigeru Katagiri, Miho Ohsaki
2017 — conf
Compact kernel classifiers trained with minimum classification error criterion.
MLSP
Ryoma Tani, Hideyuki Watanabe, Shigeru Katagiri, Miho Ohsaki
2017 J jnl
Confusion-Matrix-Based Kernel Logistic Regression for Imbalanced Data Classification.
IEEE Trans. Knowl. Data Eng.
Miho Ohsaki, Peng Wang, Kenji Matsuda, Shigeru Katagiri, Hideyuki Watanabe, Anca L. Ralescu
2015 B conf
Formulation of the kernel logistic regression based on the confusion matrix.
CEC
Miho Ohsaki, Kenji Matsuda, Peng Wang, Shigeru Katagiri, Hideyuki Watanabe
2014 J jnl
Minimum Classification Error Training Incorporating Automatic Loss Smoothness Determination.
J. Signal Process. Syst.
Hideyuki Watanabe, Jun'ichi Tokuno, Tsukasa Ohashi, Shigeru Katagiri, Miho Ohsaki, Shigeki Matsuda, Hideki Kashioka
2014 J jnl
Robust and Efficient Pattern Classification using Large Geometric Margin Minimum Classification Error Training.
J. Signal Process. Syst.
Hideyuki Watanabe, Tsukasa Ohashi, Shigeru Katagiri, Miho Ohsaki, Shigeki Matsuda, Hideki Kashioka
2012 — conf
Application of kernel logistic regression to the prediction of liver fibrosis stages in chronic hepatitis C.
SCIS&ISIS
Kenji Matsuda, Miho Ohsaki, Shigeru Katagiri, Hideto Yokoi, Katsuhiko Takabayashi
2012 Misc conf
Increasing virtual samples through loss smoothness determination in large geometric margin minimum classification error training.
ICASSP
Tsukasa Ohashi, Hideyuki Watanabe, Jun'ichi Tokuno, Shigeru Katagiri, Miho Ohsaki, Shigeki Matsuda, Hideki Kashioka
2011 — conf
Minimum classification error training with automatic setting of loss smoothness.
MLSP
Hideyuki Watanabe, Jun'ichi Tokuno, Tsukasa Ohashi, Shigeru Katagiri, Miho Ohsaki
2011 — conf
Minimum classification error training with geometric margin enhancement for robust pattern recognition.
MLSP
Hideyuki Watanabe, Shigeru Katagiri, Miho Ohsaki
2010 J jnl
Improving a rule evaluation support method based on objective indices.
Int. J. Adv. Intell. Paradigms
Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
2010 Misc conf
Minimum Error Classification with geometric margin control.
ICASSP
Hideyuki Watanabe, Shigeru Katagiri, Kouta Yamada, Erik McDermott, Atsushi Nakamura, Shinji Watanabe, Miho Ohsaki
2009 A* conf
Analysis of Subsequence Time-Series Clustering Based on Moving Average.
ICDM
Miho Ohsaki, Masakazu Nakase, Shigeru Katagiri
2009 — ch.
Evaluating Learning Algorithms Composed by a Constructive Meta-learning Scheme for a Rule Evaluation Support Method.
Mining Complex Data
Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
2009 B conf
Improvement of interactive EC fitting based on substitute evaluation using sound volume preference.
FUZZ-IEEE
Miho Ohsaki
2008 — ch.
Evaluating Learning Algorithms to Support Human Rule Evaluation with Predicting Interestingness Based on Objective Rule Evaluation Indices.
Communications and Discoveries from Multidisciplinary Data
Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
2008 — conf
Finding Functional Groups of Objective Rule Evaluation Indices Using PCA.
PAKM
Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
2007 — conf
Developing an Integrated Time-Series Data Mining Environment for Medical Data Mining.
ICDM Workshops
Hidenao Abe, Hideto Yokoi, Miho Ohsaki, Takahira Yamaguchi
2007 — conf
Evaluating Accuracies of a Trading Rule Mining Method Based on Temporal Pattern Extraction.
MCD
Hidenao Abe, Satoru Hirabayashi, Miho Ohsaki, Takahira Yamaguchi
2007 — conf
Evaluating Learning Algorithms to Construct Rule Evaluation Models Based on Objective Rule Evaluation Indices.
IEEE ICCI
Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
2007 J jnl
Evaluating Learning Algorithms to Support Human Rule - Evaluation Based on Objective Rule Evaluation Indices.
Data Sci. J.
Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
2007 — conf
Evaluating Learning Models with Transitions of Human Interests Based on Objective Rule Evaluation Indices.
MedInfo
Hidenao Abe, Hideto Yokoi, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
2007 — conf
Evaluating a Constructive Meta-learning Algorithm for a Rule Evaluation Support Method Based on Objective Indices.
KES (2)
Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
2007 B conf
Evaluating learning algorithms for a rule evaluation support method.
SMC
Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
2007 Misc conf
Evaluation of Learning Costs of Rule Evaluation Models Based on Objective Indices to Predict Human Hypothesis Construction Phases.
GrC
Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Hideto Yokoi, Takahira Yamaguchi
2007 J jnl
Evaluation of rule interestingness measures in medical knowledge discovery in databases.
Artif. Intell. Medicine
Miho Ohsaki, Hidenao Abe, Shusaku Tsumoto, Hideto Yokoi, Takahira Yamaguchi
2007 J jnl
Interactive Evolutionary Computation-Based Hearing Aid Fitting.
IEEE Trans. Evol. Comput.
Hideyuki Takagi, Miho Ohsaki
2007 J jnl
Numerical Time-Series Pattern Extraction Based on Irregular Piecewise Aggregate Approximation and Gradient Specification.
New Gener. Comput.
Miho Ohsaki, Hidenao Abe, Takahira Yamaguchi
2006 — conf
Developing a Rule Evaluation Support Method Based on Objective Indices.
RSKT
Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
2006 — conf
Evaluating Learning Algorithms Composed by a Constructive Meta-Learning Scheme for a Rule Evaluation Support Method.
ICDM Workshops
Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
2006 C conf
Evaluating Learning Algorithms for a Rule Evaluation Support Method Based on Objective Rule Evaluation Indices.
ISMIS
Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
2006 C conf
Evaluating Learning Algorithms with Meta-learning Schemes for a Rule Evaluation Support Method Based on Objective Indices.
PKAW
Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Hideto Yokoi, Takahira Yamaguchi
2006 — conf
Evaluating Learning Models for a Rule Evaluation Support Method Based on Objective Indices.
RSCTC
Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
2006 B conf
Evaluating Model Construction Methods with Objective Rule Evaluation Indices to Support Human Experts.
MDAI
Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
2006 B conf
Evaluating a Rule Evaluation Support Method Based on Objective Rule Evaluation Indices.
PAKDD
Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
2006 — conf
Proposal of Medical KDD Support User Interface Utilizing Rule Interestingness Measures.
ICDM Workshops
Miho Ohsaki, Hidenao Abe, Shusaku Tsumoto, Hideto Yokoi, Takahira Yamaguchi
2005 A* conf
A Rule Evaluation Support Method with Learning Models Based on Objective Rule Evaluation Indexes.
ICDM
Hidenao Abe, Shusaku Tsumoto, Miho Ohsaki, Takahira Yamaguchi
2005 C conf
Evaluating a Rule Evaluation Support Method with Learning Models Based on Objective Rule Evaluation Indices - A Case Study with a Meningitis Data Mining Result.
HIS
Hidenao Abe, Miho Ohsaki, Shusaku Tsumoto, Takahira Yamaguchi
2005 — conf
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.
JSAI Workshops
Hidenao Abe, Miho Ohsaki, Hideto Yokoi, Takahira Yamaguchi
2004 C conf
Comparison between Objective Interestingness Measures and Real Human Interest in Medical Data Mining.
IEA/AIE
Miho Ohsaki, Yoshinori Sato, Shinya Kitaguchi, Hideto Yokoi, Takahira Yamaguchi
2004 — conf
Evaluation of Rule Interestingness Measures with a Clinical Dataset on Hepatitis.
PKDD
Miho Ohsaki, Shinya Kitaguchi, Kazuya Okamoto, Hideto Yokoi, Takahira Yamaguchi
2003 — conf
Investigation of Rule Interestingness in Medical Data Mining.
Active Mining
Miho Ohsaki, Shinya Kitaguchi, Hideto Yokoi, Takahira Yamaguchi
2003 — conf
Sampling point extraction based on genetic algorithm and function approximation of a search space.
CIRA
Miho Ohsaki, Yoshifumi Banno, Tomohiro Yoshikawa, Tsuyoshi Shinogi, Nobuharu Tsuruoka
2000 B conf
Evaluation of edge detection methods through psychological tests-is the detected edge really desirable for humans?
SMC
Miho Ohsaki, Takahiro Sugiyama, Hideaki Ohno
1998 J jnl
An input method using discrete fitness values for interactive GA.
J. Intell. Fuzzy Syst.
Miho Ohsaki, Hideyuki Takagi, Kimiko Ohya
1998 B conf
Improvement of presenting interface by predicting the evaluation order to reduce the burden of human interactive EC operators.
SMC
Miho Ohsaki, Hideyuki Takagi