Masayuki Karasuyama

According to our database1, Masayuki Karasuyama authored at least 47 papers between 2006 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Learning Attributed Graphlets: Predictive Graph Mining by Graphlets with Trainable Attribute.
CoRR, 2024

2023
Multi-Objective Bayesian Optimization with Active Preference Learning.
CoRR, 2023

Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds.
CoRR, 2023

Randomized Gaussian Process Upper Confidence Bound with Tight Bayesian Regret Bounds.
CoRR, 2023

Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes.
Proceedings of the International Conference on Machine Learning, 2023

Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds.
Proceedings of the International Conference on Machine Learning, 2023

A stopping criterion for Bayesian optimization by the gap of expected minimum simple regrets.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Stat-DSM: Statistically Discriminative Sub-Trajectory Mining With Multiple Testing Correction.
IEEE Trans. Knowl. Data Eng., 2022

A Generalized Framework of Multifidelity Max-Value Entropy Search Through Joint Entropy.
Neural Comput., 2022

Bayesian Optimization for Cascade-Type Multistage Processes.
Neural Comput., 2022

Sequential and Parallel Constrained Max-value Entropy Search via Information Lower Bound.
Proceedings of the International Conference on Machine Learning, 2022

Bayesian Optimization for Distributionally Robust Chance-constrained Problem.
Proceedings of the International Conference on Machine Learning, 2022

2021
Distance metric learning for graph structured data.
Mach. Learn., 2021

Bayesian Optimization for Cascade-type Multi-stage Processes.
CoRR, 2021

2020
Active Learning for Level Set Estimation Under Input Uncertainty and Its Extensions.
Neural Comput., 2020

Active Learning of Bayesian Linear Models with High-Dimensional Binary Features by Parameter Confidence-Region Estimation.
Neural Comput., 2020

Cost-effective search for lower-error region in material parameter space using multifidelity Gaussian process modeling.
CoRR, 2020

Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization.
Proceedings of the 37th International Conference on Machine Learning, 2020

Multi-objective Bayesian Optimization using Pareto-frontier Entropy.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Safe Triplet Screening for Distance Metric Learning.
Neural Comput., 2019

Active learning for level set estimation under cost-dependent input uncertainty.
CoRR, 2019

Statistically Discriminative Sub-trajectory Mining.
CoRR, 2019

Multi-fidelity Bayesian Optimization with Max-value Entropy Search.
CoRR, 2019

Efficient learning algorithm for sparse subsequence pattern-based classification and applications to comparative animal trajectory data analysis.
Adv. Robotics, 2019

Learning Interpretable Metric between Graphs: Convex Formulation and Computation with Graph Mining.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Statistically Discriminative Sub-trajectory Mining with Multiple Testing Correction.
Proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2019

2018
Factor Analysis on a Graph.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Homotopy continuation approaches for robust SV classification and regression.
Mach. Learn., 2017

Adaptive edge weighting for graph-based learning algorithms.
Mach. Learn., 2017

Exploring phenotype patterns of breast cancer within somatic mutations: a modicum in the intrinsic code.
Briefings Bioinform., 2017

2016
Safe Pattern Pruning: An Efficient Approach for Predictive Pattern Mining.
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.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Regularization Path of Cross-Validation Error Lower Bounds.
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.
IEEE Trans. Neural Networks Learn. Syst., 2013

Manifold-based Similarity Adaptation for Label Propagation.
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.
Neural Networks, 2012

Multi-parametric solution-path algorithm for instance-weighted support vector machines.
Mach. Learn., 2012

2011
Nonlinear Regularization Path for Quadratic Loss Support Vector Machines.
IEEE Trans. Neural Networks, 2011

Suboptimal Solution Path Algorithm for Support Vector Machine.
Proceedings of the 28th International Conference on Machine Learning, 2011

2010
Multiple incremental decremental learning of support vector machines.
IEEE Trans. Neural Networks, 2010

Nonlinear regularization path for the modified Huber loss Support Vector Machines.
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.
New Gener. Comput., 2009

Adaptive Kernel Quantile Regression for Anomaly Detection.
J. Adv. Comput. Intell. Intell. Informatics, 2009

2008
Reducing SVR Support Vectors by Using Backward Deletion.
Proceedings of the Knowledge-Based Intelligent Information and Engineering Systems, 2008

Optimizing Sparse Kernel Ridge Regression hyperparameters based on leave-one-out cross-validation.
Proceedings of the International Joint Conference on Neural Networks, 2008

2007
Optimizing SVR Hyperparameters via Fast Cross-Validation using AOSVR.
Proceedings of the International Joint Conference on Neural Networks, 2007

2006
Revised Optimizer of SVR Hyperparameters Minimizing Cross-Validation Error.
Proceedings of the International Joint Conference on Neural Networks, 2006


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