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Masayuki Karasuyama
Masayuki Karasuyama
Verified email at nitech.ac.jp - Homepage
Title
Cited by
Cited by
Year
Multiple graph label propagation by sparse integration
M Karasuyama, H Mamitsuka
IEEE transactions on neural networks and learning systems 24 (12), 1999-2012, 2013
1252013
Multiple incremental decremental learning of support vector machines
M Karasuyama, I Takeuchi
IEEE Transactions on Neural Networks 21 (7), 1048-1059, 2010
1122010
Manifold-based similarity adaptation for label propagation
M Karasuyama, H Mamitsuka
Advances in neural information processing systems 26, 2013
662013
Machine-learning-based selective sampling procedure for identifying the low-energy region in a potential energy surface: A case study on proton conduction in oxides
K Toyoura, D Hirano, A Seko, M Shiga, A Kuwabara, M Karasuyama, ...
Physical Review B 93 (5), 054112, 2016
622016
Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization
S Takeno, H Fukuoka, Y Tsukada, T Koyama, M Shiga, I Takeuchi, ...
International Conference on Machine Learning, 9334-9345, 2020
592020
Multiple incremental decremental learning of support vector machines
M Karasuyama, I Takeuchi
Advances in neural information processing systems 22, 2009
422009
Simultaneous safe screening of features and samples in doubly sparse modeling
A Shibagaki, M Karasuyama, K Hatano, I Takeuchi
International Conference on Machine Learning, 1577-1586, 2016
412016
Multi-parametric solution-path algorithm for instance-weighted support vector machines
M Karasuyama, N Harada, M Sugiyama, I Takeuchi
Machine learning 88 (3), 297-330, 2012
402012
Safe pattern pruning: An efficient approach for predictive pattern mining
K Nakagawa, S Suzumura, M Karasuyama, K Tsuda, I Takeuchi
Proceedings of the 22nd acm sigkdd international conference on knowledge …, 2016
342016
Understanding Colour Tuning Rules and Predicting Absorption Wavelengths of Microbial Rhodopsins by Data-Driven Machine-Learning Approach
M Karasuyama, K Inoue, R Nakamura, H Kandori, I Takeuchi
Scientific reports 8 (1), 15580, 2018
322018
Multi-objective Bayesian Optimization using Pareto-frontier Entropy
S Suzuki, S Takeno, T Tamura, K Shitara, M Karasuyama
International Conference on Machine Learning, 9279-9288, 2020
292020
Exploring a potential energy surface by machine learning for characterizing atomic transport
K Kanamori, K Toyoura, J Honda, K Hattori, A Seko, M Karasuyama, ...
Physical Review B 97 (12), 125124, 2018
282018
Fast and scalable prediction of local energy at grain boundaries: machine-learning based modeling of first-principles calculations
T Tamura, M Karasuyama, R Kobayashi, R Arakawa, Y Shiihara, ...
Modelling and Simulation in Materials Science and Engineering 25 (7), 075003, 2017
272017
Canonical dependency analysis based on squared-loss mutual information
M Karasuyama, M Sugiyama
Neural Networks 34, 46-55, 2012
272012
Adaptive edge weighting for graph-based learning algorithms
M Karasuyama, H Mamitsuka
Machine Learning 106 (2), 307-335, 2017
252017
Bayesian-optimization-guided experimental search of NASICON-type solid electrolytes for all-solid-state Li-ion batteries
M Harada, H Takeda, S Suzuki, K Nakano, N Tanibata, M Nakayama, ...
Journal of Materials Chemistry A 8 (30), 15103-15109, 2020
242020
A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines
M Gönen, BA Weir, GS Cowley, F Vazquez, Y Guan, A Jaiswal, ...
Cell systems 5 (5), 485-497. e3, 2017
192017
Nonlinear regularization path for quadratic loss support vector machines
M Karasuyama, I Takeuchi
IEEE transactions on neural networks 22 (10), 1613-1625, 2011
152011
Suboptimal solution path algorithm for support vector machine
M Karasuyama, I Takeuchi
arXiv preprint arXiv:1105.0471, 2011
152011
Suboptimal Solution Path Algorithm for Support Vector Machine
IT Masayuki Karasuyama
Proceedings of the 28th International Conference on Machine Learning, 473-480, 2011
15*2011
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Articles 1–20