Approximate Reduction from AUC Maximization to 1-Norm Soft Margin Optimization. - Daiki Suehiro; Kohei Hatano; Eiji Takimoto (ALT, 2011)

Online Prediction under Submodular Constraints. - Daiki Suehiro; Kohei Hatano; Shuji Kijima; Eiji Takimoto; Kiyohito Nagano (ALT, 2012)

Face-to-Face Teaching Analytics: Extracting Teaching Activities from E-Book Logs via Time-Series Analysis. - Daiki Suehiro; Yuta Taniguchi; Atsushi Shimada 001; Hiroaki Ogata (ICALT, 2017)

Revealing Hidden Impression Topics in Students' Journals Based on Nonnegative Matrix Factorization. - Yuta Taniguchi; Daiki Suehiro; Atsushi Shimada 001; Hiroaki Ogata (ICALT, 2017)

Real-time learning analytics for C programming language courses. - Xinyu Fu 002; Atsushi Shimada 001; Hiroaki Ogata; Yuta Taniguchi; Daiki Suehiro (LAK, 2017)

Boosting the kernelized shapelets: Theory and algorithms for local features. - Daiki Suehiro; Kohei Hatano; Eiji Takimoto; Shuji Yamamoto; Kenichi Bannai; Akiko Takeda (CoRR, 2017)

Multiple-Instance Learning by Boosting Infinitely Many Shapelet-based Classifiers. - Daiki Suehiro; Kohei Hatano; Eiji Takimoto; Shuji Yamamoto; Kenichi Bannai; Akiko Takeda (CoRR, 2018)

Efficient Reformulation of 1-Norm Ranking SVM. - Daiki Suehiro; Kohei Hatano; Eiji Takimoto (IEICE Trans. Inf. Syst., 2018)

Optimal Rejection Function Meets Character Recognition Tasks. - Xiaotong Ji; Yuchen Zheng; Daiki Suehiro; Seiichi Uchida (ACPR (2), 2019)

Logo Design Analysis by Ranking. - Takuro Karamatsu; Daiki Suehiro; Seiichi Uchida (ICDAR, 2019)

RankSVM for Offline Signature Verification. - Yan Zheng; Yuchen Zheng; Wataru Ohyama; Daiki Suehiro; Seiichi Uchida (ICDAR, 2019)

An Application of Multiple-Instance Learning to Estimate Generalization Risk. - Daiki Suehiro (CoRR, 2019)

Adaptive Aggregation of Arbitrary Online Trackers with a Regret Bound. - Heon Song; Daiki Suehiro; Seiichi Uchida (WACV, 2020)

No Regret Sample Selection with Noisy Labels. - Nariaki Mitsuo; Seiichi Uchida; Daiki Suehiro (CoRR, 2020)

AAA: Adaptive Aggregation of Arbitrary Online Trackers with Theoretical Performance Guarantee. - Heon Song; Daiki Suehiro; Seiichi Uchida (CoRR, 2020)

Theory and Algorithms for Shapelet-Based Multiple-Instance Learning. - Daiki Suehiro; Kohei Hatano; Eiji Takimoto; Shuji Yamamoto; Kenichi Bannai; Akiko Takeda (Neural Comput., 2020)

Top-Rank Learning Robust to Outliers. - Yan Zheng; Daiki Suehiro; Seiichi Uchida (ICONIP (3), 2021)

Cell Detection from Imperfect Annotation by Pseudo Label Selection Using P-classification. - Kazuma Fujii; Daiki Suehiro; Kazuya Nishimura; Ryoma Bise (MICCAI (8), 2021)

Top-rank convolutional neural network and its application to medical image-based diagnosis. - Yan Zheng; Yuchen Zheng; Daiki Suehiro; Seiichi Uchida (Pattern Recognit., 2021)

Revealing Reliable Signatures by Learning Top-Rank Pairs. - Xiaotong Ji; Yan Zheng; Daiki Suehiro; Seiichi Uchida (DAS, 2022)

Simplified and unified analysis of various learning problems by reduction to Multiple-Instance Learning. - Daiki Suehiro; Eiji Takimoto (UAI, 2022)

Learning From Label Proportion with Online Pseudo-Label Decision by Regret Minimization. - Shinnosuke Matsuo; Ryoma Bise; Seiichi Uchida; Daiki Suehiro (ICASSP, 2023)

MixBag: Bag-Level Data Augmentation for Learning from Label Proportions. - Takanori Asanomi; Shinnosuke Matsuo; Daiki Suehiro; Ryoma Bise (ICCV, 2023)

Boosting for Bounding the Worst-class Error. - Yuya Saito; Shinnosuke Matsuo; Seiichi Uchida; Daiki Suehiro (CoRR, 2023)

Paired contrastive feature for highly reliable offline signature verification. - Xiaotong Ji; Daiki Suehiro; Seiichi Uchida (Pattern Recognit., 2023)

Theoretical Proportion Label Perturbation for Learning from Label Proportions in Large Bags. - Shunsuke Kubo; Shinnosuke Matsuo; Daiki Suehiro; Kazuhiro Terada; Hiroaki Ito; Akihiko Yoshizawa; Ryoma Bise (ECAI, 2024)

Counting Network for Learning from Majority Label. - Kaito Shiku; Shinnosuke Matsuo; Daiki Suehiro; Ryoma Bise (ICASSP, 2024)

Learning from Partial Label Proportions for Whole Slide Image Segmentation. - Shinnosuke Matsuo; Daiki Suehiro; Seiichi Uchida; Hiroaki Ito; Kazuhiro Terada; Akihiko Yoshizawa; Ryoma Bise (MICCAI (11), 2024)

No regret sample selection with noisy labels. - Heon Song; Nariaki Mitsuo; Seiichi Uchida; Daiki Suehiro (Mach. Learn., 2024)

Ordinal Multiple-instance Learning for Ulcerative Colitis Severity Estimation with Selective Aggregated Transformer. - Kaito Shiku; Kazuya Nishimura; Daiki Suehiro; Kiyohito Tanaka; Ryoma Bise (WACV, 2025)