Motoki Shiga

20 papers A* 2B 1C 2Journal 13Unranked 2
YearRankTypeTitle / Venue / Authors
2026 J jnl
Coordinate Encoding on Linear Grids for Physics-Informed Neural Networks.
CoRR
Tetsuro Tsuchino, Motoki Shiga
2022 J jnl
A Generalized Framework of Multifidelity Max-Value Entropy Search Through Joint Entropy.
Neural Comput.
Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama
2020 J jnl
Cost-effective search for lower-error region in material parameter space using multifidelity Gaussian process modeling.
CoRR
Shion Takeno, Yuhki Tsukada, Hitoshi Fukuoka, Toshiyuki Koyama, Motoki Shiga, Masayuki Karasuyama
2020 A* conf
Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization.
ICML
Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama
2019 J jnl
Multi-fidelity Bayesian Optimization with Max-value Entropy Search.
CoRR
Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama
2015 J jnl
Direct conditional probability density estimation with sparse feature selection.
Mach. Learn.
Motoki Shiga, Voot Tangkaratt, Masashi Sugiyama
2015 J jnl
Non-Negative Matrix Factorization with Auxiliary Information on Overlapping Groups.
IEEE Trans. Knowl. Data Eng.
Motoki Shiga, Hiroshi Mamitsuka
2014 J jnl
Detecting Differentially Coexpressed Genesfrom Labeled Expression Data: A Brief Review.
IEEE ACM Trans. Comput. Biol. Bioinform.
Mitsunori Kayano, Motoki Shiga, Hiroshi Mamitsuka
2013 — conf
Variational Bayes co-clustering with auxiliary information.
MultiClust@KDD
Motoki Shiga, Hiroshi Mamitsuka
2012 J jnl
A Variational Bayesian Framework for Clustering with Multiple Graphs.
IEEE Trans. Knowl. Data Eng.
Motoki Shiga, Hiroshi Mamitsuka
2012 J jnl
Efficient semi-supervised learning on locally informative multiple graphs.
Pattern Recognit.
Motoki Shiga, Hiroshi Mamitsuka
2011 J jnl
A spectral approach to clustering numerical vectors as nodes in a network.
Pattern Recognit.
Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka
2011 J jnl
Clustering genes with expression and beyond.
WIREs Data Mining Knowl. Discov.
Motoki Shiga, Hiroshi Mamitsuka
2009 J jnl
Efficiently finding genome-wide three-way gene interactions from transcript- and genotype-data.
Bioinform.
Mitsunori Kayano, Ichigaku Takigawa, Motoki Shiga, Koji Tsuda, Hiroshi Mamitsuka
2009 J jnl
Upper bound for variational free energy of Bayesian networks.
Mach. Learn.
Kazuho Watanabe, Motoki Shiga, Sumio Watanabe
2008 C conf
Mining significant tree patterns in carbohydrate sugar chains.
ECCB
Kosuke Hashimoto, Ichigaku Takigawa, Motoki Shiga, Minoru Kanehisa, Hiroshi Mamitsuka
2007 A* conf
A spectral clustering approach to optimally combining numericalvectors with a modular network.
KDD
Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka
2007 — conf
Annotating gene function by combining expression data with a modular gene network.
ISMB/ECCB (Supplement of Bioinformatics)
Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka
2006 C conf
Upper Bounds for Variational Stochastic Complexities of Bayesian Networks.
IDEAL
Kazuho Watanabe, Motoki Shiga, Sumio Watanabe
2005 B conf
An optimal entropy estimator for discrete random variables.
IJCNN
Motoki Shiga, Yasunari Yokota