Sumio Watanabe

106 papers A* 2A 1B 9C 4Misc 1Journal 54Unranked 34

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Review and Prospect of Algebraic Research in Equivalent Framework between Statistical Mechanics and Machine Learning Theory. CoRR Sumio Watanabe
2023	J	`jnl`	Bayesian Free Energy of Deep ReLU Neural Network in Overparametrized Cases. CoRR Shuya Nagayasu, Sumio Watanabe
2023	C	`conf`	Free Energy of Bayesian Convolutional Neural Network with Skip Connection. ACML Shuya Nagayasu, Sumio Watanabe
2023	J	`jnl`	Free energy of Bayesian Convolutional Neural Network with Skip Connection. CoRR Shuya Nagayasu, Sumio Watanabe
2023	J	`jnl`	Upper Bound of Real Log Canonical Threshold of Tensor Decomposition and its Application to Bayesian Inference. CoRR Naoki Yoshida, Sumio Watanabe
2022	J	`jnl`	Asymptotic Behavior of Bayesian Generalization Error in Multinomial Mixtures. CoRR Takumi Watanabe, Sumio Watanabe
2022	J	`jnl`	Asymptotic behavior of free energy when optimal probability distribution is not unique. Neurocomputing Shuya Nagayasu, Sumio Watanabe
2022	J	`jnl`	Mathematical Theory of Bayesian Statistics for Unknown Information Source. CoRR Sumio Watanabe
2022	J	`jnl`	Recent Advances in Algebraic Geometry and Bayesian Statistics. CoRR Sumio Watanabe
2020	J	`jnl`	Asymptotic Bayesian Generalization Error in Latent Dirichlet Allocation and Stochastic Matrix Factorization. SN Comput. Sci. Naoki Hayashi, Sumio Watanabe
2020	J	`jnl`	Testing Homogeneity for Normal Mixture Models: Variational Bayes Approach. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. Natsuki Kariya, Sumio Watanabe
2017	—	`conf`	Phase Transition Structure of Variational Bayesian Nonnegative Matrix Factorization. ICANN (2) Masahiro Kohjima, Sumio Watanabe
2017	—	`conf`	Tighter upper bound of real log canonical threshold of non-negative matrix factorization and its application to Bayesian inference. SSCI Naoki Hayashi, Sumio Watanabe
2017	J	`jnl`	Upper Bound of Bayesian Generalization Error in Stochastic Matrix Factorization. CoRR Naoki Hayashi, Sumio Watanabe
2017	J	`jnl`	Upper bound of Bayesian generalization error in non-negative matrix factorization. Neurocomputing Naoki Hayashi, Sumio Watanabe
2016	C	`conf`	Interpretation Method of Nonlinear Multilayer Principal Component Analysis by Using Sparsity and Hierarchical Clustering. ICMLA Natsuki Koda, Sumio Watanabe
2016	J	`jnl`	Upper Bound of Bayesian Generalization Error in Non-negative Matrix Factorization. CoRR Naoki Hayashi, Sumio Watanabe
2015	J	`jnl`	Bayesian Cross Validation and WAIC for Predictive Prior Design in Regular Asymptotic Theory. CoRR Sumio Watanabe
2013	—	`conf`	A Geometric Evaluation of Self-Organizing Map and Application to City Data Analysis. MIWAI Shigehiro Ohara, Keisuke Yamazaki, Sumio Watanabe
2013	J	`jnl`	A widely applicable Bayesian information criterion. J. Mach. Learn. Res. Sumio Watanabe
2012	J	`jnl`	A Widely Applicable Bayesian Information Criterion CoRR Sumio Watanabe
2012	—	`conf`	Information criterion for variational Bayes learning in regular and singular cases. SCIS&ISIS Koshi Yamada, Sumio Watanabe
2012	J	`jnl`	Statistical Learning Theory of Quasi-Regular Cases. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. Koshi Yamada, Sumio Watanabe
2012	J	`jnl`	Stochastic complexity of Bayesian networks CoRR Keisuke Yamazaki, Sumio Watanabe
2011	J	`jnl`	Two design methods of hyperparameters in variational Bayes learning for Bernoulli mixtures. Neurocomputing Daisuke Kaji, Sumio Watanabe
2010	J	`jnl`	Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory CoRR Sumio Watanabe
2010	J	`jnl`	Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory. J. Mach. Learn. Res. Sumio Watanabe
2010	J	`jnl`	Asymptotic Learning Curve and Renormalizable Condition in Statistical Learning Theory CoRR Sumio Watanabe
2010	J	`jnl`	Asymptotic analysis of Bayesian generalization error with Newton diagram. Neural Networks Keisuke Yamazaki, Miki Aoyagi, Sumio Watanabe
2010	J	`jnl`	Equations of States in Statistical Learning for an Unrealizable and Regular Case. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. Sumio Watanabe
2010	J	`jnl`	Equations of states in singular statistical estimation. Neural Networks Sumio Watanabe
2010	—	`conf`	On Generalization Error of Self-Organizing Map. ICONIP (2) Fumiaki Saitoh, Sumio Watanabe
2010	J	`jnl`	Phase Transition of Variational Bayes Learning in Bernoulli Mixture. Aust. J. Intell. Inf. Process. Syst. Daisuke Kaji, Kazuho Watanabe, Sumio Watanabe
2009	J	`jnl`	A Limit Theorem in Singular Regression Problem CoRR Sumio Watanabe
2009	J	`jnl`	Accuracy of Loopy belief propagation in Gaussian models. Neural Networks Yu Nishiyama, Sumio Watanabe
2009	J	`jnl`	Equations of States in Statistical Learning for a Nonparametrizable and Regular Case CoRR Sumio Watanabe
2009	—	`conf`	Optimal Hyperparameters for Generalized Learning and Knowledge Discovery in Variational Bayes. ICONIP (1) Daisuke Kaji, Sumio Watanabe
2009	J	`jnl`	Upper bound for variational free energy of Bayesian networks. Mach. Learn. Kazuho Watanabe, Motoki Shiga, Sumio Watanabe
2008	B	`conf`	A formula of equations of states in singular learning machines. IJCNN Sumio Watanabe
2008	J	`jnl`	Asymptotic behavior of exchange ratio in exchange Monte Carlo method. Neural Networks Kenji Nagata, Sumio Watanabe
2008	—	`conf`	Design of Exchange Monte Carlo Method for Bayesian Learning in Normal Mixture Models. ICONIP (1) Kenji Nagata, Sumio Watanabe
2008	J	`jnl`	Exchange Monte Carlo Sampling From Bayesian Posterior for Singular Learning Machines. IEEE Trans. Neural Networks Kenji Nagata, Sumio Watanabe
2008	—	`conf`	Experimental Study of Ergodic Learning Curve in Hidden Markov Models. ICONIP (1) Masashi Matsumoto, Sumio Watanabe
2008	—	`conf`	Generalization of Concave and Convex Decomposition in Kikuchi Free Energy. ICANN (1) Yu Nishiyama, Sumio Watanabe
2008	—	`conf`	Model Selection Method for AdaBoost Using Formal Information Criteria. ICONIP (2) Daisuke Kaji, Sumio Watanabe
2008	Misc	`conf`	On the Minima of Bethe Free Energy in Gaussian Distributions. ICAISC Yu Nishiyama, Sumio Watanabe
2007	—	`conf`	Algebraic Geometric Study of Exchange Monte Carlo Method. ICANN (1) Kenji Nagata, Sumio Watanabe
2007	—	`conf`	Almost All Learning Machines are Singular. FOCI Sumio Watanabe
2007	—	`conf`	Analysis of Exchange Ratio for Exchange Monte Carlo Method. FOCI Kenji Nagata, Sumio Watanabe
2007	A*	`conf`	Asymptotic Bayesian generalization error when training and test distributions are different. ICML Keisuke Yamazaki, Motoaki Kawanabe, Sumio Watanabe, Masashi Sugiyama, Klaus-Robert Müller
2007	J	`jnl`	Equations of States in Singular Statistical Estimation CoRR Sumio Watanabe
2007	—	`conf`	Estimation of Poles of Zeta Function in Learning Theory Using Padé Approximation. ICANN (1) Ryosuke Iriguchi, Sumio Watanabe
2007	—	`conf`	Experimental Analysis of Exchange Ratio in Exchange Monte Carlo Method. ICONIP (2) Kenji Nagata, Sumio Watanabe
2007	—	`conf`	Experimental Bayesian Generalization Error of Non-regular Models under Covariate Shift. ICONIP (1) Keisuke Yamazaki, Sumio Watanabe
2007	—	`conf`	Generalization Error of Automatic Relevance Determination. ICANN (1) Shinichi Nakajima, Sumio Watanabe
2007	—	`conf`	On a Singular Point to Contribute to a Learning Coefficient and Weighted Resolution of Singularities. ICANN (1) Takeshi Matsuda, Sumio Watanabe
2007	B	`conf`	Resolution of Singularities and Stochastic Complexity of Complete Bipartite Graph-Type Spin Model in Bayesian Estimation. MDAI Miki Aoyagi, Sumio Watanabe
2007	J	`jnl`	Stochastic complexities of general mixture models in variational Bayesian learning. Neural Networks Kazuho Watanabe, Sumio Watanabe
2007	J	`jnl`	Stochastic complexity for mixture of exponential families in generalized variational Bayes. Theor. Comput. Sci. Kazuho Watanabe, Sumio Watanabe
2007	—	`conf`	The Calculation Method of Learning Coefficients by Weighted Resolution of Singularities. MLMTA Takeshi Matsuda, Sumio Watanabe
2007	—	`conf`	Theoretical Analysis of Accuracy of Gaussian Belief Propagation. ICANN (1) Yu Nishiyama, Sumio Watanabe
2007	J	`jnl`	Variational Bayes Solution of Linear Neural Networks and Its Generalization Performance. Neural Comput. Shinichi Nakajima, Sumio Watanabe
2006	—	`conf`	A Model Selection Method Based on Bound of Learning Coefficient. ICANN (2) Keisuke Yamazaki, Kenji Nagata, Sumio Watanabe, Klaus-Robert Müller
2006	—	`conf`	Analytic Equivalence of Bayes a Posteriori Distributions. ICANN (1) Takeshi Matsuda, Sumio Watanabe
2006	—	`conf`	Analytic Solution of Hierarchical Variational Bayes in Linear Inverse Problem. ICANN (2) Shinichi Nakajima, Sumio Watanabe
2006	—	`conf`	Asymptotic Behavior of Stochastic Complexity of Complete Bipartite Graph-Type Boltzmann Machines. ICONIP (1) Yu Nishiyama, Sumio Watanabe
2006	—	`conf`	Free Energy of Stochastic Context Free Grammar on Variational Bayes. ICONIP (1) Tikara Hosino, Kazuho Watanabe, Sumio Watanabe
2006	C	`conf`	Generalization Performance of Exchange Monte Carlo Method for Normal Mixture Models. IDEAL Kenji Nagata, Sumio Watanabe
2006	J	`jnl`	Generalization Performance of Subspace Bayes Approach in Linear Neural Networks. IEICE Trans. Inf. Syst. Shinichi Nakajima, Sumio Watanabe
2006	—	`conf`	Generalization error of three layered learning model in bayesian estimation. Computational Intelligence Miki Aoyagi, Sumio Watanabe
2006	—	`conf`	Localized Bayes Estimation for Non-identifiable Models. ICONIP (1) Shingo Takamatsu, Shinichi Nakajima, Sumio Watanabe
2006	J	`jnl`	Stochastic Complexities of Gaussian Mixtures in Variational Bayesian Approximation. J. Mach. Learn. Res. Kazuho Watanabe, Sumio Watanabe
2006	B	`conf`	The Exchange Monte Carlo Method for Bayesian Learning in Singular Learning Machines. IJCNN Kenji Nagata, Sumio Watanabe
2006	C	`conf`	Upper Bounds for Variational Stochastic Complexities of Bayesian Networks. IDEAL Kazuho Watanabe, Motoki Shiga, Sumio Watanabe
2005	J	`jnl`	Algebraic geometry and stochastic complexity of hidden Markov models. Neurocomputing Keisuke Yamazaki, Sumio Watanabe
2005	J	`jnl`	Algebraic geometry of singular learning machines and symmetry of generalization and training errors. Neurocomputing Sumio Watanabe
2005	A*	`conf`	Generalization Error of Linear Neural Networks in an Empirical Bayes Approach. IJCAI Shinichi Nakajima, Sumio Watanabe
2005	J	`jnl`	Singularities in complete bipartite graph-type Boltzmann machines and upper bounds of stochastic complexities. IEEE Trans. Neural Networks Keisuke Yamazaki, Sumio Watanabe
2005	B	`conf`	Stochastic Complexity for Mixture of Exponential Families in Variational Bayes. ALT Kazuho Watanabe, Sumio Watanabe
2005	J	`jnl`	Stochastic complexities of reduced rank regression in Bayesian estimation. Neural Networks Miki Aoyagi, Sumio Watanabe
2005	B	`conf`	Stochastic complexity of variational Bayesian hidden Markov models. IJCNN Tikara Hosino, Kazuho Watanabe, Sumio Watanabe
2005	—	`conf`	Variational Bayesian Stochastic Complexity of Mixture Models. NIPS Kazuho Watanabe, Sumio Watanabe
2004	B	`conf`	Estimation of the Data Region Using Extreme-Value Distributions. ALT Kazuho Watanabe, Sumio Watanabe
2004	B	`conf`	Newton Diagram and Stochastic Complexity in Mixture of Binomial Distributions. ALT Keisuke Yamazaki, Sumio Watanabe
2003	J	`jnl`	Learning Coefficients of Layered Models When the True Distribution Mismatches the Singularities. Neural Comput. Sumio Watanabe, Shun-ichi Amari
2003	J	`jnl`	Singularities in mixture models and upper bounds of stochastic complexity. Neural Networks Keisuke Yamazaki, Sumio Watanabe
2003	A	`conf`	Stochastic Complexity of Bayesian Networks. UAI Keisuke Yamazaki, Sumio Watanabe
2003	—	`conf`	Stochastic complexities of hidden Markov models. NNSP Keisuke Yamazaki, Sumio Watanabe
2002	J	`jnl`	Errata to "learning efficiency of redundant neural networks in bayesian estimation". IEEE Trans. Neural Networks Sumio Watanabe
2002	—	`conf`	The Effect of Singularities in a Learning Machine when the True Parameters Do Not Lie on such Singularities. NIPS Sumio Watanabe, Shun-ichi Amari
2001	J	`jnl`	Algebraic Analysis for Nonidentifiable Learning Machines. Neural Comput. Sumio Watanabe
2001	J	`jnl`	Algebraic geometrical methods for hierarchical learning machines. Neural Networks Sumio Watanabe
2001	J	`jnl`	Learning efficiency of redundant neural networks in Bayesian estimation. IEEE Trans. Neural Networks Sumio Watanabe
2000	—	`conf`	Algebraic Information Geometry for Learning Machines with Singularities. NIPS Sumio Watanabe
1999	—	`conf`	Algebraic Analysis for Non-regular Learning Machines. NIPS Sumio Watanabe
1999	B	`conf`	Algebraic Analysis for Singular Statistical Estimation. ALT Sumio Watanabe
1998	B	`conf`	Inequalities of Generalization Errors for Layered Neural Networks in Bayesian Learning. ICONIP Sumio Watanabe
1998	—	`ch.`	Probabilistic design. Algorithms and Architectures Sumio Watanabe, Kenji Fukumizu
1996	J	`jnl`	A network of chaotic elements for information processing. Neural Networks Shin Ishii, Kenji Fukumizu, Sumio Watanabe
1996	J	`jnl`	Solvable models of layered neural networks based on their differential structure. Adv. Comput. Math. Sumio Watanabe
1995	J	`jnl`	A Modified Information Criterion for Automatic Model and Parameter Selection in Neural Network Learning. IEICE Trans. Inf. Syst. Sumio Watanabe
1995	J	`jnl`	Genetic algorithms applied to bayesian image restoration. Syst. Comput. Jpn. Kazunori Takatsu, Hidefumi Sawai, Sumio Watanabe, Masahide Yoneyama
1995	J	`jnl`	Probabilistic design of layered neural networks based on their unified framework. IEEE Trans. Neural Networks Sumio Watanabe, Kenji Fukumizu
1993	—	`conf`	An Optimization Method of Layered Neural Networks based on the Modified Information Criterion. NIPS Sumio Watanabe
1993	—	`conf`	Solvable Models of Artificial Neural Networks. NIPS Sumio Watanabe
1992	J	`jnl`	An ultrasonic visual sensor for three-dimensional object recognition using neural networks. IEEE Trans. Robotics Autom. Sumio Watanabe, Masahide Yoneyama