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2020 – today
- 2022
[j10]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): 2145-2203 (2022)- 2020
- [c6]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: 9334-9345 - [i2]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 abs/2003.13428 (2020)
2010 – 2019
- 2019
- [i1]Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama:
Multi-fidelity Bayesian Optimization with Max-value Entropy Search. CoRR abs/1901.08275 (2019) - 2015
- [j9]Motoki Shiga, Voot Tangkaratt, Masashi Sugiyama:
Direct conditional probability density estimation with sparse feature selection. Mach. Learn. 100(2-3): 161-182 (2015) - [j8]Motoki Shiga, Hiroshi Mamitsuka:
Non-Negative Matrix Factorization with Auxiliary Information on Overlapping Groups. IEEE Trans. Knowl. Data Eng. 27(6): 1615-1628 (2015) - 2014
- [j7]Mitsunori Kayano, Motoki Shiga, Hiroshi Mamitsuka:
Detecting Differentially Coexpressed Genesfrom Labeled Expression Data: A Brief Review. IEEE ACM Trans. Comput. Biol. Bioinform. 11(1): 154-167 (2014) - 2013
- [c5]Motoki Shiga, Hiroshi Mamitsuka:
Variational Bayes co-clustering with auxiliary information. MultiClust@KDD 2013: 5 - 2012
- [j6]Motoki Shiga, Hiroshi Mamitsuka:
Efficient semi-supervised learning on locally informative multiple graphs. Pattern Recognit. 45(3): 1035-1049 (2012) - [j5]Motoki Shiga, Hiroshi Mamitsuka:
A Variational Bayesian Framework for Clustering with Multiple Graphs. IEEE Trans. Knowl. Data Eng. 24(4): 577-590 (2012) - 2011
- [j4]Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka:
A spectral approach to clustering numerical vectors as nodes in a network. Pattern Recognit. 44(2): 236-251 (2011) - [j3]Motoki Shiga, Hiroshi Mamitsuka:
Clustering genes with expression and beyond. WIREs Data Mining Knowl. Discov. 1(6): 496-511 (2011)
2000 – 2009
- 2009
- [j2]Mitsunori Kayano, Ichigaku Takigawa, Motoki Shiga, Koji Tsuda, Hiroshi Mamitsuka:
Efficiently finding genome-wide three-way gene interactions from transcript- and genotype-data. Bioinform. 25(21): 2735-2743 (2009) - [j1]Kazuho Watanabe, Motoki Shiga, Sumio Watanabe:
Upper bound for variational free energy of Bayesian networks. Mach. Learn. 75(2): 199-215 (2009) - 2008
- [c4]Kosuke Hashimoto, Ichigaku Takigawa, Motoki Shiga, Minoru Kanehisa, Hiroshi Mamitsuka:
Mining significant tree patterns in carbohydrate sugar chains. ECCB 2008: 167-173 - 2007
- [c3]Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka:
Annotating gene function by combining expression data with a modular gene network. ISMB/ECCB (Supplement of Bioinformatics) 2007: 468-478 - [c2]Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka:
A spectral clustering approach to optimally combining numericalvectors with a modular network. KDD 2007: 647-656 - 2006
- [c1]Kazuho Watanabe, Motoki Shiga, Sumio Watanabe:
Upper Bounds for Variational Stochastic Complexities of Bayesian Networks. IDEAL 2006: 139-146
Coauthor Index
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