Masayuki Karasuyama

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 43

Top Topics

Active Learning

Upper Confidence Bound

Top Venues

Publications

Ryota Ozaki, Kazuki Ishikawa, Youhei Kanzaki, Shion Takeno, Ichiro Takeuchi, Masayuki Karasuyama
Multi-Objective Bayesian Optimization with Active Preference Learning. AAAI (2024)
Tajima Shinji, Ren Sugihara, Ryota Kitahara, Masayuki Karasuyama
Learning Attributed Graphlets: Predictive Graph Mining by Graphlets with Trainable Attribute. CoRR (2024)
Tajima Shinji, Ren Sugihara, Ryota Kitahara, Masayuki Karasuyama
Learning Attributed Graphlets: Predictive Graph Mining by Graphlets with Trainable Attribute. KDD (2024)
Shion Takeno, Masahiro Nomura, Masayuki Karasuyama
Hot off the Press: Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes. GECCO Companion (2024)
Shion Takeno, Masahiro Nomura, Masayuki Karasuyama
Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes. CoRR (2023)
Shion Takeno, Yu Inatsu, Masayuki Karasuyama
Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds. ICML (2023)
Hideaki Ishibashi, Masayuki Karasuyama, Ichiro Takeuchi, Hideitsu Hino
A stopping criterion for Bayesian optimization by the gap of expected minimum simple regrets. AISTATS (2023)
Ryota Ozaki, Kazuki Ishikawa, Youhei Kanzaki, Shinya Suzuki, Shion Takeno, Ichiro Takeuchi, Masayuki Karasuyama
Multi-Objective Bayesian Optimization with Active Preference Learning. CoRR (2023)
Shion Takeno, Yu Inatsu, Masayuki Karasuyama, Ichiro Takeuchi
Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds. CoRR (2023)
Shion Takeno, Yu Inatsu, Masayuki Karasuyama
Randomized Gaussian Process Upper Confidence Bound with Tight Bayesian Regret Bounds. CoRR (2023)
Shion Takeno, Masahiro Nomura, Masayuki Karasuyama
Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes. ICML (2023)
Yu Inatsu, Shion Takeno, Masayuki Karasuyama, Ichiro Takeuchi
Bayesian Optimization for Distributionally Robust Chance-constrained Problem. CoRR (2022)
Yu Inatsu, Shion Takeno, Masayuki Karasuyama, Ichiro Takeuchi
Bayesian Optimization for Distributionally Robust Chance-constrained Problem. ICML (2022)
Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama
A Generalized Framework of Multifidelity Max-Value Entropy Search Through Joint Entropy. Neural Comput. 34 (10) (2022)
Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, Masayuki Karasuyama
Sequential and Parallel Constrained Max-value Entropy Search via Information Lower Bound. ICML (2022)
Vo Nguyen Le Duy, Takuto Sakuma, Taiju Ishiyama, Hiroki Toda, Kazuya Arai, Masayuki Karasuyama, Yuta Okubo, Masayuki Sunaga, Hiroyuki Hanada, Yasuo Tabei, Ichiro Takeuchi
Stat-DSM: Statistically Discriminative Sub-Trajectory Mining With Multiple Testing Correction. IEEE Trans. Knowl. Data Eng. 34 (3) (2022)
Shunya Kusakawa, Shion Takeno, Yu Inatsu, Kentaro Kutsukake, Shogo Iwazaki, Takashi Nakano, Toru Ujihara, Masayuki Karasuyama, Ichiro Takeuchi
Bayesian Optimization for Cascade-Type Multistage Processes. Neural Comput. 34 (12) (2022)
Tomoki Yoshida, Ichiro Takeuchi, Masayuki Karasuyama
Distance metric learning for graph structured data. Mach. Learn. 110 (7) (2021)
Shunya Kusakawa, Shion Takeno, Yu Inatsu, Kentaro Kutsukake, Shogo Iwazaki, Takashi Nakano, Toru Ujihara, Masayuki Karasuyama, Ichiro Takeuchi
Bayesian Optimization for Cascade-type Multi-stage Processes. CoRR (2021)
Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, Masayuki Karasuyama
Sequential- and Parallel- Constrained Max-value Entropy Search via Information Lower Bound. CoRR (2021)
Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama
Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization. ICML (2020)
Yu Inatsu, Masayuki Karasuyama, Keiichi Inoue, Ichiro Takeuchi
Active Learning for Level Set Estimation Under Input Uncertainty and Its Extensions. Neural Comput. 32 (12) (2020)
Tomoki Yoshida, Ichiro Takeuchi, Masayuki Karasuyama
Distance Metric Learning for Graph Structured Data. CoRR (2020)
Shion Takeno, Yuhki Tsukada, Hitoshi Fukuoka, Toshiyuki Koyama, Motoki Shiga, Masayuki Karasuyama
Cost-effective search for lower-error region in material parameter space using multifidelity Gaussian process modeling. CoRR (2020)
Yu Inatsu, Masayuki Karasuyama, Keiichi Inoue, Hideki Kandori, Ichiro Takeuchi
Active Learning of Bayesian Linear Models with High-Dimensional Binary Features by Parameter Confidence-Region Estimation. Neural Comput. 32 (10) (2020)
Shinya Suzuki, Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, Masayuki Karasuyama
Multi-objective Bayesian Optimization using Pareto-frontier Entropy. ICML (2020)
Tomoki Yoshida, Ichiro Takeuchi, Masayuki Karasuyama
Safe Triplet Screening for Distance Metric Learning. Neural Comput. 31 (12) (2019)
Vo Nguyen Le Duy, Takuto Sakuma, Taiju Ishiyama, Hiroki Toda, Kazuya Arai, Masayuki Karasuyama, Yuta Okubo, Masayuki Sunaga, Yasuo Tabei, Ichiro Takeuchi
Statistically Discriminative Sub-trajectory Mining with Multiple Testing Correction. SIGSPATIAL/GIS (2019)
Takuto Sakuma, Kazuya Nishi, Kaoru Kishimoto, Kazuya Nakagawa, Masayuki Karasuyama, Yuta Umezu, Shinsuke Kajioka, Shuhei J. Yamazaki, Koutarou D. Kimura, Sakiko Matsumoto, Ken Yoda, Matasaburo Fukutomi, Hisashi Shidara, Hiroto Ogawa, Ichiro Takeuchi
Efficient learning algorithm for sparse subsequence pattern-based classification and applications to comparative animal trajectory data analysis. Adv. Robotics 33 (3-4) (2019)
Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama
Multi-fidelity Bayesian Optimization with Max-value Entropy Search. CoRR (2019)
Vo Nguyen Le Duy, Takuto Sakuma, Taiju Ishiyama, Hiroki Toda, Kazuya Nishi, Masayuki Karasuyama, Yuta Okubo, Masayuki Sunaga, Yasuo Tabei, Ichiro Takeuchi
Statistically Discriminative Sub-trajectory Mining. CoRR (2019)
Tomoki Yoshida, Ichiro Takeuchi, Masayuki Karasuyama
Learning Interpretable Metric between Graphs: Convex Formulation and Computation with Graph Mining. KDD (2019)
Yu Inatsu, Masayuki Karasuyama, Keiichi Inoue, Ichiro Takeuchi
Active learning for level set estimation under cost-dependent input uncertainty. CoRR (2019)
Shinya Suzuki, Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, Masayuki Karasuyama
Multi-objective Bayesian Optimization using Pareto-frontier Entropy. CoRR (2019)
Tomoki Yoshida, Ichiro Takeuchi, Masayuki Karasuyama
Safe Triplet Screening for Distance Metric Learning. KDD (2018)
Masayuki Karasuyama, Hiroshi Mamitsuka
Factor Analysis on a Graph. AISTATS (2018)
Sohiya Yotsukura, Masayuki Karasuyama, Ichigaku Takigawa, Hiroshi Mamitsuka
Exploring phenotype patterns of breast cancer within somatic mutations: a modicum in the intrinsic code. Briefings Bioinform. 18 (4) (2017)
Shinya Suzumura, Kohei Ogawa, Masashi Sugiyama, Masayuki Karasuyama, Ichiro Takeuchi
Homotopy continuation approaches for robust SV classification and regression. Mach. Learn. 106 (7) (2017)
Masayuki Karasuyama, Hiroshi Mamitsuka
Adaptive edge weighting for graph-based learning algorithms. Mach. Learn. 106 (2) (2017)
Atsushi Shibagaki, Masayuki Karasuyama, Kohei Hatano, Ichiro Takeuchi
Simultaneous Safe Screening of Features and Samples in Doubly Sparse Modeling. ICML (2016)
Kazuya Nakagawa, Shinya Suzumura, Masayuki Karasuyama, Koji Tsuda, Ichiro Takeuchi
Safe Pattern Pruning: An Efficient Approach for Predictive Pattern Mining. KDD (2016)
Atsushi Shibagaki, Yoshiki Suzuki, Masayuki Karasuyama, Ichiro Takeuchi
Regularization Path of Cross-Validation Error Lower Bounds. NIPS (2015)
Shinya Suzumura, Kohei Ogawa, Masashi Sugiyama, Masayuki Karasuyama, Ichiro Takeuchi
Homotopy Continuation Approaches for Robust SV Classification and Regression. CoRR (2015)
Masayuki Karasuyama, Hiroshi Mamitsuka
Multiple Graph Label Propagation by Sparse Integration. IEEE Trans. Neural Networks Learn. Syst. 24 (12) (2013)
Masayuki Karasuyama, Hiroshi Mamitsuka
Manifold-based Similarity Adaptation for Label Propagation. NIPS (2013)
Masayuki Karasuyama, Masashi Sugiyama
Canonical dependency analysis based on squared-loss mutual information. Neural Networks 34 (2012)
Masayuki Karasuyama, Naoyuki Harada, Masashi Sugiyama, Ichiro Takeuchi
Multi-parametric solution-path algorithm for instance-weighted support vector machines. Mach. Learn. 88 (3) (2012)
Masayuki Karasuyama, Ichiro Takeuchi
Suboptimal Solution Path Algorithm for Support Vector Machine CoRR (2011)
Masayuki Karasuyama, Ichiro Takeuchi
Nonlinear Regularization Path for Quadratic Loss Support Vector Machines. IEEE Trans. Neural Networks 22 (10) (2011)
Masayuki Karasuyama, Ichiro Takeuchi
Suboptimal Solution Path Algorithm for Support Vector Machine. ICML (2011)
Masayuki Karasuyama, Naoyuki Harada, Masashi Sugiyama, Ichiro Takeuchi
Multi-parametric solution-path algorithm for instance-weighted support vector machines. MLSP (2011)
Masayuki Karasuyama, Naoyuki Harada, Masashi Sugiyama, Ichiro Takeuchi
Multi-parametric Solution-path Algorithm for Instance-weighted Support Vector Machines CoRR (2010)
Masayuki Karasuyama, Ichiro Takeuchi
Nonlinear regularization path for the modified Huber loss Support Vector Machines. IJCNN (2010)
Masayuki Karasuyama, Ichiro Takeuchi
Multiple incremental decremental learning of support vector machines. IEEE Trans. Neural Networks 21 (7) (2010)
Masayuki Karasuyama, Ichiro Takeuchi, Ryohei Nakano
-out Cross-Validation of Support Vector Regression by Generalizing Decremental Algorithm. New Gener. Comput. 27 (4) (2009)
Hiroyuki Moriguchi, Ichiro Takeuchi, Masayuki Karasuyama, Shin-ichi Horikawa, Yoshikatsu Ohta, Tetsuji Kodama, Hiroshi Naruse
Adaptive Kernel Quantile Regression for Anomaly Detection. J. Adv. Comput. Intell. Intell. Informatics 13 (3) (2009)
Masayuki Karasuyama, Ichiro Takeuchi
Multiple Incremental Decremental Learning of Support Vector Machines. NIPS (2009)
Masayuki Karasuyama, Ichiro Takeuchi, Ryohei Nakano
Reducing SVR Support Vectors by Using Backward Deletion. KES (3) (2008)
Masayuki Karasuyama, Ryohei Nakano
Optimizing Sparse Kernel Ridge Regression hyperparameters based on leave-one-out cross-validation. IJCNN (2008)
Masayuki Karasuyama, Ryohei Nakano
Optimizing SVR Hyperparameters via Fast Cross-Validation using AOSVR. IJCNN (2007)
Masayuki Karasuyama, Daisuke Kitakoshi, Ryohei Nakano
Revised Optimizer of SVR Hyperparameters Minimizing Cross-Validation Error. IJCNN (2006)