Keisuke Yamazaki

发表

A Model Selection Method Based on Bound of Learning Coefficient

Klaus-Robert Müller, Sumio Watanabe, Keisuke Yamazaki, 2006, ICANN.

Stochastic complexities of hidden Markov models

Sumio Watanabe, Keisuke Yamazaki, 2003, 2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718).

Hidden Node Detection between Observable Nodes Based on Bayesian Clustering

Keisuke Yamazaki, Yoichi Motomura, Y. Motomura, 2017, AMBN.

Asymptotic accuracy of Bayes estimation for latent variables with redundancy

Keisuke Yamazaki, 2015, Machine Learning.

Kernel Recursive ABC: Point Estimation with Intractable Likelihood

Kenji Fukumizu, Keisuke Yamazaki, Motonobu Kanagawa, 2018, ICML.

MCMC sampling on latent-variable space of mixture of probabilistic PCA

Keisuke Yamazaki, 2012, The 6th International Conference on Soft Computing and Intelligent Systems, and The 13th International Symposium on Advanced Intelligence Systems.

Accuracy of latent-variable estimation in Bayesian semi-supervised learning

Keisuke Yamazaki, Keisuke Yamazaki, K. Yamazaki, 2013, Neural Networks.

Asymptotic Bayesian generalization error when training and test distributions are different

Motoaki Kawanabe, Klaus-Robert Müller, Masashi Sugiyama, 2007, ICML '07.

Experimental Bayesian Generalization Error of Non-regular Models under Covariate Shift

Sumio Watanabe, Keisuke Yamazaki, 2007, ICONIP.

A Probabilistic Algorithm to Calculate the Learning Curves of Hierarchical Learning Machines with Singularities

Sumio Watanabe, Keisuke Yamazaki, Sumio Watanabe, 2002 .

Stochastic Complexity and Singularities in Hierarchical Bayesian Networks

Sumio Watanabe, Keisuke Yamazaki, Sumio Watanabe, 2004 .

Asymptotic Accuracy of Bayesian Estimation for a Single Latent Variable

Keisuke Yamazaki, K. Yamazaki, 2014, Neural Networks.

Singularities in mixture models and upper bounds of stochastic complexity

Sumio Watanabe, Keisuke Yamazaki, 2003, Neural Networks.

Asymptotic Marginal Likelihood on Linear Dynamical Systems

Keisuke Yamazaki, Takuto Naito, 2014, IEICE Trans. Inf. Syst..

Accuracy analysis of semi-supervised classification when the class balance changes

Keisuke Yamazaki, Keisuke Yamazaki, K. Yamazaki, 2015, Neurocomputing.

Algebraic geometry and stochastic complexity of hidden Markov models

Sumio Watanabe, Keisuke Yamazaki, 2005, Neurocomputing.

On the likelihood function of HMMs for a long data sequence

Keisuke Yamazaki, 2009, 2009 IEEE International Workshop on Machine Learning for Signal Processing.

Newton Diagram and Stochastic Complexity in Mixture of Binomial Distributions

Sumio Watanabe, Keisuke Yamazaki, 2004, ALT.

A Risk Information Provision System on Bicycle Parking Lots

Keisuke Yamazaki, Tsuyoshi Nakajima, 2017, 2017 IEEE International Congress on Internet of Things (ICIOT).

Accuracy of latent variable estimation with the maximum likelihood estimator for partially observed hidden data

Keisuke Yamazaki, Keisuke Yamazaki, K. Yamazaki, 2012, 2012 International Symposium on Information Theory and its Applications.

Parameter estimation accuracy and active learning in the zero-range process

Koichi Kobayashi, Keisuke Yamazaki, Keisuke Yamazaki, 2012, 2012 12th International Conference on Intelligent Systems Design and Applications (ISDA).

An Analysis of Generalization Error in Relevant Subtask Learning

Samuel Kaski, Keisuke Yamazaki, Samuel Kaski, 2008, ICONIP.

Asymptotic accuracy of distribution-based estimation of latent variables

Keisuke Yamazaki, Keisuke Yamazaki, K. Yamazaki, 2012, J. Mach. Learn. Res..

On asymmetric generalization error of asymmetric multitask learning

Samuel Kaski, Keisuke Yamazaki, S. Kaski, 2008 .

Effects of additional data on Bayesian clustering

Keisuke Yamazaki, Keisuke Yamazaki, K. Yamazaki, 2016, Neural Networks.

Development of a new type surface actuator

Keisuke Yamazaki, Toshio Shimizu, Gunji Kimura, 1994, Proceedings of IECON'94 - 20th Annual Conference of IEEE Industrial Electronics.

Model Bridging: To Interpretable Simulation Model From Neural Network pdf

Keisuke Yamazaki, Keiichi Kisamori, 2019, ArXiv.

Comparing two Bayes methods based on the free energy functions in Bernoulli mixtures

Keisuke Yamazaki, Daisuke Kaji, 2013, Neural Networks.

Modeling and Grouping of Optimal Speeds Based on Traffic-Flow Video

Keisuke Yamazaki, Fumito Nakamura, 2015 .

Asymptotic analysis of Bayesian generalization error with Newton diagram

Sumio Watanabe, Keisuke Yamazaki, Miki Aoyagi, 2010, Neural Networks.

An asymptotic analysis of Bayesian state estimation in hidden Markov models

Keisuke Yamazaki, K. Yamazaki, 2011, 2011 IEEE International Workshop on Machine Learning for Signal Processing.

Stochastic Complexity of Bayesian Networks pdf

Sumio Watanabe, Keisuke Yamazaki, 2003, UAI.

Generative approximation of generalization error

Keisuke Yamazaki, 2009, 2009 IEEE International Workshop on Machine Learning for Signal Processing.

A Study on Bayesian Learning of One-Dimensional Linear Dynamical Systems

Keisuke Yamazaki, Takuto Naito, 2009, ICONIP.

On Bayesian Clustering with a Structured Gaussian Mixture

Keisuke Yamazaki, Keisuke Yamazaki, 2014, J. Adv. Comput. Intell. Intell. Informatics.

Development of an Integrated AI Platform and an Ecosystem for Daily Life, Business and Social Problems

Keisuke Yamazaki, Yoichi Motomura, Kazuya Yamashita, 2018 .

A Geometric Evaluation of Self-Organizing Map and Application to City Data Analysis

Sumio Watanabe, Keisuke Yamazaki, Shigehiro Ohara, 2013, MIWAI.

Bayesian estimation of multidimensional latent variables and its asymptotic accuracy

Keisuke Yamazaki, 2018, Neural Networks.

Singularities in complete bipartite graph-type Boltzmann machines and upper bounds of stochastic complexities

Sumio Watanabe, Keisuke Yamazaki, 2005, IEEE Transactions on Neural Networks.

Intractable Likelihood Regression for Covariate Shift by Kernel Mean Embedding pdf

Keisuke Yamazaki, Keiichi Kisamori, Keisuke Yamazaki, 2018, ArXiv.

Two statistical methods for grouping vehicles in traffic flow based on probabilistic cellular automata

Keisuke Yamazaki, Fumito Nakamura, 2014, 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS).

The optimal hyperparameter for Bayesian clustering and its application to the evaluation of clustering results

Keisuke Yamazaki, 2014, 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems (SCIS) and 15th International Symposium on Advanced Intelligent Systems (ISIS).

Model Bridging: Connection between Simulation Model and Neural Network

Keisuke Yamazaki, Yuto Komori, Hiroshi Tokieda, 2019 .

On equivalent parameter learning in simplified feature space based on Bayesian asymptotic analysis

Keisuke Yamazaki, 2012, Neural Networks.

Simulator Calibration under Covariate Shift with Kernels

Keisuke Yamazaki, Motonobu Kanagawa, Keiichi Kisamori, 2020, AISTATS.

Detecting Competitive Behaviors in Conflicts

Daichi Yanagisawa, Keisuke Yamazaki, D. Yanagisawa, 2017, Traffic and Granular Flow '17.

On the Optimal Hyperparameter Behavior in Bayesian Clustering

Keisuke Yamazaki, 2015, J. Adv. Comput. Intell. Intell. Informatics.

Detecting aggressive agents in egress process by using conflict data in cellular automaton model

Daichi Yanagisawa, Keisuke Yamazaki, D. Yanagisawa, 2021, J. Intell. Transp. Syst..