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2020 – today
- 2023
[c25]Lincon S. Souza, Bojan Batalo
, Keisuke Yamazaki:
A Geometric Surrogate for Simulation Calibration. ICASSP 2023: 1-5- 2022
- [c24]Yoriyuki Yamagata, Shunki Takami, Keisuke Yamazaki, Tomoki Nakaya, Masaki Onishi:
Individual-based epidemiological model of COVID19 using location data. IEEE Big Data 2022: 4434-4442 - [c23]Keisuke Yamazaki, Satoshi Tamura, Yuuto Gotoh, Masaki Nose:
Visual-only Voice Activity Detection using Human Motion in Conference Video. ICPRAM 2022: 570-577 - [c22]Tomoya Kitamura, Atsumi Saito, Keisuke Yamazaki, Yuki Saito, Hiroshi Asai, Kouhei Ohnishi:
Validation of a Property Estimation Method Based on Sequential and Posteriori Estimation. IECON 2022: 1-6 - 2021
- [j18]Daichi Yanagisawa, Keisuke Yamazaki:
Detecting aggressive agents in egress process by using conflict data in cellular automaton model. J. Intell. Transp. Syst. 25(6): 626-643 (2021) - [c21]Rina Komatsu, Keisuke Yamazaki:
Conditional Drive Environment Translation using StarGAN with CBIN. AICCC 2021: 53-61 - 2020
- [c20]Keiichi Kisamori, Motonobu Kanagawa, Keisuke Yamazaki:
Simulator Calibration under Covariate Shift with Kernels. AISTATS 2020: 1244-1253 - [c19]Keiichi Kisamori, Keisuke Yamazaki, Yuto Komori, Hiroshi Tokieda:
Model Bridging: Connection Between Simulation Model and Neural Network. ECML/PKDD (5) 2020: 389-405
2010 – 2019
- 2019
- [j17]Keisuke Yamazaki, Yoichi Motomura:
Hidden Node Detection between Observable Nodes Based on Bayesian Clustering. Entropy 21(1): 32 (2019) - [i5]Keiichi Kisamori, Keisuke Yamazaki:
Model Bridging: To Interpretable Simulation Model From Neural Network. CoRR abs/1906.09391 (2019) - 2018
- [j16]Keisuke Yamazaki:
Bayesian estimation of multidimensional latent variables and its asymptotic accuracy. Neural Networks 105: 14-25 (2018) - [c18]Takafumi Kajihara, Motonobu Kanagawa, Keisuke Yamazaki, Kenji Fukumizu:
Kernel Recursive ABC: Point Estimation with Intractable Likelihood. ICML 2018: 2405-2414 - [i4]Keiichi Kisamori, Keisuke Yamazaki:
Intractable Likelihood Regression for Covariate Shift by Kernel Mean Embedding. CoRR abs/1809.08159 (2018) - 2017
- [j15]Keisuke Yamazaki:
Effects of additional data on Bayesian clustering. Neural Networks 94: 86-95 (2017) - [c17]Keisuke Yamazaki, Yoichi Motomura:
Hidden Node Detection between Two Observable Nodes Based on Bayesian Clustering. AMBN 2017: 165-175 - [c16]Keisuke Yamazaki, Tsuyoshi Nakajima:
A Risk Information Provision System on Bicycle Parking Lots. ICIOT 2017: 162-165 - 2016
- [j14]Keisuke Yamazaki:
Asymptotic accuracy of Bayes estimation for latent variables with redundancy. Mach. Learn. 102(1): 1-28 (2016) - 2015
- [j13]Keisuke Yamazaki:
Accuracy analysis of semi-supervised classification when the class balance changes. Neurocomputing 160: 132-140 (2015) - [j12]Keisuke Yamazaki:
On the Optimal Hyperparameter Behavior in Bayesian Clustering. J. Adv. Comput. Intell. Intell. Informatics 19(6): 818-824 (2015) - [j11]Keisuke Yamazaki:
Accuracy of latent-variable estimation in Bayesian semi-supervised learning. Neural Networks 69: 1-10 (2015) - [j10]Keisuke Yamazaki:
Asymptotic accuracy of Bayesian estimation for a single latent variable. Neural Networks 69: 11-19 (2015) - 2014
- [j9]Takuto Naito, Keisuke Yamazaki:
Asymptotic Marginal Likelihood on Linear Dynamical Systems. IEICE Trans. Inf. Syst. 97-D(4): 884-892 (2014) - [j8]Keisuke Yamazaki:
On Bayesian Clustering with a Structured Gaussian Mixture. J. Adv. Comput. Intell. Intell. Informatics 18(6): 1007-1012 (2014) - [j7]Keisuke Yamazaki:
Asymptotic accuracy of distribution-based estimation of latent variables. J. Mach. Learn. Res. 15(1): 3541-3562 (2014) - [c15]Fumito Nakamura, Keisuke Yamazaki:
Two statistical methods for grouping vehicles in traffic flow based on probabilistic cellular automata. SCIS&ISIS 2014: 956-960 - [c14]Keisuke Yamazaki:
The optimal hyperparameter for Bayesian clustering and its application to the evaluation of clustering results. SCIS&ISIS 2014: 961-965 - [i3]Keisuke Yamazaki:
Asymptotic Accuracy of Bayesian Estimation for a Single Latent Variable. CoRR abs/1408.5661 (2014) - 2013
- [j6]Keisuke Yamazaki, Daisuke Kaji:
Comparing two Bayes methods based on the free energy functions in Bernoulli mixtures. Neural Networks 44: 36-43 (2013) - [c13]Shigehiro Ohara, Keisuke Yamazaki, Sumio Watanabe:
A Geometric Evaluation of Self-Organizing Map and Application to City Data Analysis. MIWAI 2013: 165-174 - 2012
- [j5]Keisuke Yamazaki:
On equivalent parameter learning in simplified feature space based on Bayesian asymptotic analysis. Neural Networks 31: 73-80 (2012) - [c12]Koichi Kobayashi, Keisuke Yamazaki:
Parameter estimation accuracy and active learning in the zero-range process. ISDA 2012: 811-814 - [c11]Keisuke Yamazaki:
Accuracy of latent variable estimation with the maximum likelihood estimator for partially observed hidden data. ISITA 2012: 707-711 - [c10]Keisuke Yamazaki:
MCMC sampling on latent-variable space of mixture of probabilistic PCA. SCIS&ISIS 2012: 1508-1513 - [i2]Keisuke Yamazaki:
Asymptotic Accuracy of Distribution-Based Estimation for Latent Variables. CoRR abs/1204.2069 (2012) - [i1]Keisuke Yamazaki, Sumio Watanabe:
Stochastic complexity of Bayesian networks. CoRR abs/1212.2511 (2012) - 2011
- [c9]Keisuke Yamazaki:
An asymptotic analysis of Bayesian state estimation in hidden Markov models. MLSP 2011: 1-6 - 2010
- [j4]Keisuke Yamazaki, Miki Aoyagi, Sumio Watanabe:
Asymptotic analysis of Bayesian generalization error with Newton diagram. Neural Networks 23(1): 35-43 (2010)
2000 – 2009
- 2009
- [c8]Takuto Naito, Keisuke Yamazaki:
A Study on Bayesian Learning of One-Dimensional Linear Dynamical Systems. ICONIP (1) 2009: 110-117 - 2008
- [c7]Keisuke Yamazaki, Samuel Kaski:
An Analysis of Generalization Error in Relevant Subtask Learning. ICONIP (1) 2008: 629-637 - 2007
- [c6]Keisuke Yamazaki, Motoaki Kawanabe, Sumio Watanabe, Masashi Sugiyama, Klaus-Robert Müller:
Asymptotic Bayesian generalization error when training and test distributions are different. ICML 2007: 1079-1086 - [c5]Keisuke Yamazaki, Sumio Watanabe:
Experimental Bayesian Generalization Error of Non-regular Models under Covariate Shift. ICONIP (1) 2007: 466-476 - 2006
- [c4]Keisuke Yamazaki, Kenji Nagata, Sumio Watanabe, Klaus-Robert Müller:
A Model Selection Method Based on Bound of Learning Coefficient. ICANN (2) 2006: 371-380 - 2005
- [j3]Keisuke Yamazaki, Sumio Watanabe:
Algebraic geometry and stochastic complexity of hidden Markov models. Neurocomputing 69(1-3): 62-84 (2005) - [j2]Keisuke Yamazaki, Sumio Watanabe:
Singularities in complete bipartite graph-type Boltzmann machines and upper bounds of stochastic complexities. IEEE Trans. Neural Networks 16(2): 312-324 (2005) - 2004
- [c3]Keisuke Yamazaki, Sumio Watanabe:
Newton Diagram and Stochastic Complexity in Mixture of Binomial Distributions. ALT 2004: 350-364 - 2003
- [j1]Keisuke Yamazaki, Sumio Watanabe:
Singularities in mixture models and upper bounds of stochastic complexity. Neural Networks 16(7): 1029-1038 (2003) - [c2]Keisuke Yamazaki, Sumio Watanabe:
Stochastic complexities of hidden Markov models. NNSP 2003: 179-188 - [c1]Keisuke Yamazaki, Sumio Watanabe:
Stochastic Complexity of Bayesian Networks. UAI 2003: 592-599
Coauthor Index
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