| 2025 | ICML | Pareto-frontier Entropy Search with Variational Lower Bound Maximization. | Masanori Ishikura, Masayuki Karasuyama |
| 2025 | KDD | Bayesian Optimization for Simultaneous Selection of Machine Learning Algorithms and Hyperparameters on Shared Latent Space. | Kazuki Ishikawa, Ryota Ozaki, Yohei Kanzaki, Ichiro Takeuchi, Masayuki Karasuyama |
| 2024 | AAAI | Multi-Objective Bayesian Optimization with Active Preference Learning. | Ryota Ozaki, Kazuki Ishikawa, Youhei Kanzaki, Shion Takeno, Ichiro Takeuchi, Masayuki Karasuyama |
| 2024 | GECCO | Hot off the Press: Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes. | Shion Takeno, Masahiro Nomura, Masayuki Karasuyama |
| 2024 | ICML | Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds. | Shion Takeno, Yu Inatsu, Masayuki Karasuyama, Ichiro Takeuchi |
| 2024 | KDD | Learning Attributed Graphlets: Predictive Graph Mining by Graphlets with Trainable Attribute. | Tajima Shinji, Ren Sugihara, Ryota Kitahara, Masayuki Karasuyama |
| 2023 | AISTATS | A stopping criterion for Bayesian optimization by the gap of expected minimum simple regrets. | Hideaki Ishibashi, Masayuki Karasuyama, Ichiro Takeuchi, Hideitsu Hino |
| 2023 | ICML | Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds. | Shion Takeno, Yu Inatsu, Masayuki Karasuyama |
| 2023 | ICML | Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes. | Shion Takeno, Masahiro Nomura, Masayuki Karasuyama |
| 2022 | ICML | Bayesian Optimization for Distributionally Robust Chance-constrained Problem. | Yu Inatsu, Shion Takeno, Masayuki Karasuyama, Ichiro Takeuchi |
| 2022 | ICML | Sequential and Parallel Constrained Max-value Entropy Search via Information Lower Bound. | Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, Masayuki Karasuyama |
| 2020 | ICML | Multi-objective Bayesian Optimization using Pareto-frontier Entropy. | Shinya Suzuki, Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, Masayuki Karasuyama |
| 2020 | ICML | Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization. | Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama |
| 2019 | KDD | Learning Interpretable Metric between Graphs: Convex Formulation and Computation with Graph Mining. | Tomoki Yoshida, Ichiro Takeuchi, Masayuki Karasuyama |
| 2018 | AISTATS | Factor Analysis on a Graph. | Masayuki Karasuyama, Hiroshi Mamitsuka |
| 2018 | KDD | Safe Triplet Screening for Distance Metric Learning. | Tomoki Yoshida, Ichiro Takeuchi, Masayuki Karasuyama |
| 2016 | ICML | Simultaneous Safe Screening of Features and Samples in Doubly Sparse Modeling. | Atsushi Shibagaki, Masayuki Karasuyama, Kohei Hatano, Ichiro Takeuchi |
| 2016 | KDD | Safe Pattern Pruning: An Efficient Approach for Predictive Pattern Mining. | Kazuya Nakagawa, Shinya Suzumura, Masayuki Karasuyama, Koji Tsuda, Ichiro Takeuchi |
| 2011 | ICML | Suboptimal Solution Path Algorithm for Support Vector Machine. | Masayuki Karasuyama, Ichiro Takeuchi |
| 2010 | IJCNN | Nonlinear regularization path for the modified Huber loss Support Vector Machines. | Masayuki Karasuyama, Ichiro Takeuchi |
| 2008 | IJCNN | Optimizing Sparse Kernel Ridge Regression hyperparameters based on leave-one-out cross-validation. | Masayuki Karasuyama, Ryohei Nakano |
| 2008 | KES | Reducing SVR Support Vectors by Using Backward Deletion. | Masayuki Karasuyama, Ichiro Takeuchi, Ryohei Nakano |
| 2007 | IJCNN | Optimizing SVR Hyperparameters via Fast Cross-Validation using AOSVR. | Masayuki Karasuyama, Ryohei Nakano |
| 2006 | IJCNN | Revised Optimizer of SVR Hyperparameters Minimizing Cross-Validation Error. | Masayuki Karasuyama, Daisuke Kitakoshi, Ryohei Nakano |