Masayuki Karasuyama

According to our database, Masayuki Karasuyama authored at least 50 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Regret Analysis for Randomized Gaussian Process Upper Confidence Bound.

Shion Takeno, Yu Inatsu, Masayuki Karasuyama

CoRR, 2024

Learning Attributed Graphlets: Predictive Graph Mining by Graphlets with Trainable Attribute.

Tajima Shinji, Ren Sugihara, Ryota Kitahara, Masayuki Karasuyama

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds.

Shion Takeno, Yu Inatsu, Masayuki Karasuyama, Ichiro Takeuchi

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Hot off the Press: Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes.

Shion Takeno, Masahiro Nomura, Masayuki Karasuyama

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

Multi-Objective Bayesian Optimization with Active Preference Learning.

Ryota Ozaki, Kazuki Ishikawa, Youhei Kanzaki, Shion Takeno, Ichiro Takeuchi, Masayuki Karasuyama

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Multi-Objective Bayesian Optimization with Active Preference Learning.

Ryota Ozaki, Kazuki Ishikawa, Youhei Kanzaki, Shinya Suzuki, Shion Takeno, Ichiro Takeuchi, Masayuki Karasuyama

CoRR, 2023

Randomized Gaussian Process Upper Confidence Bound with Tight Bayesian Regret Bounds.

Shion Takeno, Yu Inatsu, Masayuki Karasuyama

CoRR, 2023

Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes.

Shion Takeno, Masahiro Nomura, Masayuki Karasuyama

Proceedings of the International Conference on Machine Learning, 2023

Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds.

Shion Takeno, Yu Inatsu, Masayuki Karasuyama

Proceedings of the International Conference on Machine Learning, 2023

A stopping criterion for Bayesian optimization by the gap of expected minimum simple regrets.

Hideaki Ishibashi, Masayuki Karasuyama, Ichiro Takeuchi, Hideitsu Hino

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Stat-DSM: Statistically Discriminative Sub-Trajectory Mining With Multiple Testing Correction.

Vo Nguyen Le Duy, Takuto Sakuma, Taiju Ishiyama, Hiroki Toda, Kazuya Arai, Masayuki Karasuyama, Yuta Okubo, Masayuki Sunaga, Hiroyuki Hanada, Yasuo Tabei, Ichiro Takeuchi

IEEE Trans. Knowl. Data Eng., 2022

A Generalized Framework of Multifidelity Max-Value Entropy Search Through Joint Entropy.

Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama

Neural Comput., 2022

Bayesian Optimization for Cascade-Type Multistage Processes.

Shunya Kusakawa, Shion Takeno, Yu Inatsu, Kentaro Kutsukake, Shogo Iwazaki, Takashi Nakano, Toru Ujihara, Masayuki Karasuyama, Ichiro Takeuchi

Neural Comput., 2022

Sequential and Parallel Constrained Max-value Entropy Search via Information Lower Bound.

Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, Masayuki Karasuyama

Proceedings of the International Conference on Machine Learning, 2022

Bayesian Optimization for Distributionally Robust Chance-constrained Problem.

Yu Inatsu, Shion Takeno, Masayuki Karasuyama, Ichiro Takeuchi

Proceedings of the International Conference on Machine Learning, 2022

2021

Distance metric learning for graph structured data.

Tomoki Yoshida, Ichiro Takeuchi, Masayuki Karasuyama

Mach. Learn., 2021

Bayesian Optimization for Cascade-type Multi-stage Processes.

Shunya Kusakawa, Shion Takeno, Yu Inatsu, Kentaro Kutsukake, Shogo Iwazaki, Takashi Nakano, Toru Ujihara, Masayuki Karasuyama, Ichiro Takeuchi

CoRR, 2021

2020

Active Learning for Level Set Estimation Under Input Uncertainty and Its Extensions.

Yu Inatsu, Masayuki Karasuyama, Keiichi Inoue, Ichiro Takeuchi

Neural Comput., 2020

Active Learning of Bayesian Linear Models with High-Dimensional Binary Features by Parameter Confidence-Region Estimation.

Yu Inatsu, Masayuki Karasuyama, Keiichi Inoue, Hideki Kandori, Ichiro Takeuchi

Neural Comput., 2020

Cost-effective search for lower-error region in material parameter space using multifidelity Gaussian process modeling.

Shion Takeno, Yuhki Tsukada, Hitoshi Fukuoka, Toshiyuki Koyama, Motoki Shiga, Masayuki Karasuyama

CoRR, 2020

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

Proceedings of the 37th International Conference on Machine Learning, 2020

Multi-objective Bayesian Optimization using Pareto-frontier Entropy.

Shinya Suzuki, Shion Takeno, Tomoyuki Tamura, Kazuki Shitara, Masayuki Karasuyama

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Safe Triplet Screening for Distance Metric Learning.

Tomoki Yoshida, Ichiro Takeuchi, Masayuki Karasuyama

Neural Comput., 2019

Active learning for level set estimation under cost-dependent input uncertainty.

Yu Inatsu, Masayuki Karasuyama, Keiichi Inoue, Ichiro Takeuchi

CoRR, 2019

Statistically Discriminative Sub-trajectory Mining.

Vo Nguyen Le Duy, Takuto Sakuma, Taiju Ishiyama, Hiroki Toda, Kazuya Nishi, Masayuki Karasuyama, Yuta Okubo, Masayuki Sunaga, Yasuo Tabei, Ichiro Takeuchi

CoRR, 2019

Multi-fidelity Bayesian Optimization with Max-value Entropy Search.

Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama

CoRR, 2019

Efficient learning algorithm for sparse subsequence pattern-based classification and applications to comparative animal trajectory data analysis.

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

Adv. Robotics, 2019

Learning Interpretable Metric between Graphs: Convex Formulation and Computation with Graph Mining.

Tomoki Yoshida, Ichiro Takeuchi, Masayuki Karasuyama

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Statistically Discriminative Sub-trajectory Mining with Multiple Testing Correction.

Vo Nguyen Le Duy, Takuto Sakuma, Taiju Ishiyama, Hiroki Toda, Kazuya Arai, Masayuki Karasuyama, Yuta Okubo, Masayuki Sunaga, Yasuo Tabei, Ichiro Takeuchi

Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2019

2018

Factor Analysis on a Graph.

Masayuki Karasuyama, Hiroshi Mamitsuka

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Homotopy continuation approaches for robust SV classification and regression.

Shinya Suzumura, Kohei Ogawa, Masashi Sugiyama, Masayuki Karasuyama, Ichiro Takeuchi

Mach. Learn., 2017

Adaptive edge weighting for graph-based learning algorithms.

Masayuki Karasuyama, Hiroshi Mamitsuka

Mach. Learn., 2017

Exploring phenotype patterns of breast cancer within somatic mutations: a modicum in the intrinsic code.

Sohiya Yotsukura, Masayuki Karasuyama, Ichigaku Takigawa, Hiroshi Mamitsuka

Briefings Bioinform., 2017

2016

Safe Pattern Pruning: An Efficient Approach for Predictive Pattern Mining.

Kazuya Nakagawa, Shinya Suzumura, Masayuki Karasuyama, Koji Tsuda, Ichiro Takeuchi

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

Simultaneous Safe Screening of Features and Samples in Doubly Sparse Modeling.

Atsushi Shibagaki, Masayuki Karasuyama, Kohei Hatano, Ichiro Takeuchi

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Regularization Path of Cross-Validation Error Lower Bounds.

Atsushi Shibagaki, Yoshiki Suzuki, Masayuki Karasuyama, Ichiro Takeuchi

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2013

Multiple Graph Label Propagation by Sparse Integration.

Masayuki Karasuyama, Hiroshi Mamitsuka

IEEE Trans. Neural Networks Learn. Syst., 2013

Manifold-based Similarity Adaptation for Label Propagation.

Masayuki Karasuyama, Hiroshi Mamitsuka

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012

Canonical dependency analysis based on squared-loss mutual information.

Masayuki Karasuyama, Masashi Sugiyama

Neural Networks, 2012

Multi-parametric solution-path algorithm for instance-weighted support vector machines.

Masayuki Karasuyama, Naoyuki Harada, Masashi Sugiyama, Ichiro Takeuchi

Mach. Learn., 2012

2011

Nonlinear Regularization Path for Quadratic Loss Support Vector Machines.

Masayuki Karasuyama, Ichiro Takeuchi

IEEE Trans. Neural Networks, 2011

Suboptimal Solution Path Algorithm for Support Vector Machine.

Masayuki Karasuyama, Ichiro Takeuchi

Proceedings of the 28th International Conference on Machine Learning, 2011

2010

Multiple incremental decremental learning of support vector machines.

Masayuki Karasuyama, Ichiro Takeuchi

IEEE Trans. Neural Networks, 2010

Nonlinear regularization path for the modified Huber loss Support Vector Machines.

Masayuki Karasuyama, Ichiro Takeuchi

Proceedings of the International Joint Conference on Neural Networks, 2010

2009

Efficient Leave-<i>m</i>-out Cross-Validation of Support Vector Regression by Generalizing Decremental Algorithm.

Masayuki Karasuyama, Ichiro Takeuchi, Ryohei Nakano

New Gener. Comput., 2009

Adaptive Kernel Quantile Regression for Anomaly Detection.

Hiroyuki Moriguchi, Ichiro Takeuchi, Masayuki Karasuyama, Shin-ichi Horikawa, Yoshikatsu Ohta, Tetsuji Kodama, Hiroshi Naruse

J. Adv. Comput. Intell. Intell. Informatics, 2009

2008

Reducing SVR Support Vectors by Using Backward Deletion.

Masayuki Karasuyama, Ichiro Takeuchi, Ryohei Nakano

Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2008

Optimizing Sparse Kernel Ridge Regression hyperparameters based on leave-one-out cross-validation.

Masayuki Karasuyama, Ryohei Nakano

Proceedings of the International Joint Conference on Neural Networks, 2008

2007

Optimizing SVR Hyperparameters via Fast Cross-Validation using AOSVR.

Masayuki Karasuyama, Ryohei Nakano

Proceedings of the International Joint Conference on Neural Networks, 2007

2006

Revised Optimizer of SVR Hyperparameters Minimizing Cross-Validation Error.

Masayuki Karasuyama, Daisuke Kitakoshi, Ryohei Nakano

Proceedings of the International Joint Conference on Neural Networks, 2006