Joe Suzuki

Generating author description...

All published works

Action	Title	Year	Authors
+	Learning under singularity: an information criterion improving WBIC and sBIC	2024	Lirui Liu Joe Suzuki
+ PDF Chat	Generalization of LiNGAM that Allows Confounding	2024	Joe Suzuki Tian-Le Yang
+	Newton-Type Methods with the Proximal Gradient Step for Sparse Estimation	2024	Ryosuke Shimmura Joe Suzuki
+ PDF Chat	Functional linear non-Gaussian acyclic model for causal discovery	2024	Tian-Le Yang Kuang‐Yao Lee Kun Zhang Joe Suzuki
+ PDF Chat	Learning under Singularity: An Information Criterion improving WBIC and sBIC	2024	Lirui Liu Joe Suzuki
+ PDF Chat	Generalization of LiNGAM that allows confounding	2024	Joe Suzuki Tian-Le Yang
+	Functional Linear Non-Gaussian Acyclic Model for Causal Discovery	2024	Tian-Le Yang Kuang‐Yao Lee Kun Zhang Joe Suzuki
+ PDF Chat	Estimation of a Simple Structure in a Multidimensional IRT Model Using Structure Regularization	2023	Ryosuke Shimmura Joe Suzuki
+ PDF Chat	Newton-type Methods with the Proximal Gradient Step for Sparse Estimation	2023	Ryosuke Shimmura Joe Suzuki
+ PDF Chat	Extending Hilbert–Schmidt Independence Criterion for Testing Conditional Independence	2023	Bingyuan Zhang Joe Suzuki
+	Dropout Drops Double Descent	2023	Tian-Le Yang Joe Suzuki
+	Post-Selection Inference for Sparse Estimation	2023	Joe Suzuki
+	MCMC and Stan	2023	Joe Suzuki
+	Overview of Watanabe’s Bayes	2023	Joe Suzuki
+	WAIC and WBIC with R Stan	2023	Joe Suzuki
+	Regular Statistical Models	2023	Joe Suzuki
+	Introduction to Watanabe Bayesian Theory	2023	Joe Suzuki
+	MCMC and Stan	2023	Joe Suzuki
+	Introduction to Watanabe Bayesian Theory	2023	Joe Suzuki
+	Regular Statistical Models	2023	Joe Suzuki
+	Overview of Watanabe’s Bayes	2023	Joe Suzuki
+ PDF Chat	Converting ADMM to a proximal gradient for efficient sparse estimation	2022	Ryosuke Shimmura Joe Suzuki
+	Kernel Computations	2022	Joe Suzuki
+	Reproducing Kernel Hilbert Space	2022	Joe Suzuki
+	The MMD and HSIC	2022	Joe Suzuki
+	The MMD and HSIC	2022	Joe Suzuki
+	Newton-type Methods with the Proximal Gradient Step for Sparse Estimation	2022	Ryosuke Shimmura Joe Suzuki
+ PDF Chat	Efficient Proximal Gradient Algorithms for Joint Graphical Lasso	2021	Jie Chen Ryosuke Shimmura Joe Suzuki
+ PDF Chat	Causal order identification to address confounding: binary variables	2021	Joe Suzuki Yusuke Inaoka
+	Efficient proximal gradient algorithms for joint graphical lasso	2021	Jie Chen Ryosuke Shimmura Joe Suzuki
+	Converting ADMM to a Proximal Gradient for Convex Optimization Problems	2021	Ryosuke Shimmura Joe Suzuki
+	Why <scp>BDeu</scp>? Regular Bayesian network structure learning with discrete and continuous variables	2021	Joe Suzuki
+	Generalized Linear Regression	2021	Joe Suzuki
+	Causal Order Identification to Address Confounding: Binary Variables	2021	Joe Suzuki Yusuke Inaoka
+	Matrix Decomposition	2021	Joe Suzuki
+	Group Lasso	2021	Joe Suzuki
+	Generalized Linear Regression	2021	Joe Suzuki
+	Fused Lasso	2021	Joe Suzuki
+	Linear Regression	2021	Joe Suzuki
+	Linear Regression	2021	Joe Suzuki
+	Sparse Estimation with Math and R	2021	Joe Suzuki
+	Group Lasso	2021	Joe Suzuki
+	Decision Trees	2021	Joe Suzuki
+	Converting ADMM to a Proximal Gradient for Efficient Sparse Estimation	2021	Ryosuke Shimmura Joe Suzuki
+	Nonlinear Regression	2020	Joe Suzuki
+	Linear Regression	2020	Joe Suzuki
+	Decision Trees	2020	Joe Suzuki
+	Mutual Information Estimation: Independence Detection and Consistency	2019	Joe Suzuki
+ PDF Chat	Forest Learning From Data and its Universal Coding	2018	Joe Suzuki
+	Forest Learning from Data and its Universal Coding	2018	Joe Suzuki
+ PDF Chat	Klein's Fundamental 2-Form of Second Kind for the C<sub>ab</sub> Curves	2017	Joe Suzuki
+ PDF Chat	A theoretical analysis of the BDeu scores in Bayesian network structure learning	2016	Joe Suzuki
+ PDF Chat	An Estimator of Mutual Information and its Application to Independence Testing	2016	Joe Suzuki
+	A Theoretical Analysis of the BDeu Scores in Bayesian Network Structure Learning	2016	Joe Suzuki
+	A Bayesian Estimator of Mutual Information and its Application to Tests of Independence	2015	Joe Suzuki
+	Miura: Divisor Class Group Arithmetic	2015	Joe Suzuki
+	Rates of convergence of the universal Bayesian measure for continuous data	2014	Ayano Takanori Joe Suzuki
+	Causal Discovery in a Binary Exclusive-or Skew Acyclic Model: BExSAM	2014	Takanori Inazumi Takashi Washio Shohei Shimizu Joe Suzuki Akihiro Yamamoto Yoshinobu Kawahara
+	Universal Bayesian Measures and Universal Histogram Sequences	2014	Joe Suzuki
+	Identifiability of an Integer Modular Acyclic Additive Noise Model and its Causal Structure Discovery	2014	Joe Suzuki Takanori Inazumi Takashi Washio Shohei Shimizu
+	Causal Discovery in a Binary Exclusive-or Skew Acyclic Model: BExSAM	2014	Takanori Inazumi Takashi Washio Shohei Shimizu Joe Suzuki Akihiro Yamamoto Yoshinobu Kawahara
+	Universal Bayesian measures	2013	Joe Suzuki
+	MDL/Bayesian Criteria Based on Universal Coding/Measure	2013	Joe Suzuki
+	A Construction of Bayesian Networks from Databases Based on an MDL Principle	2013	Joe Suzuki
+ PDF Chat	The Hannan-Quinn Proposition for Linear Regression	2012	Joe Suzuki
+	Bayesian Network Structure Estimation Based on the Bayesian/MDL Criteria When Both Discrete and Continuous Variables Are Present	2012	Joe Suzuki
+	Discovering causal structures in binary exclusive-or skew acyclic models	2012	Takanori Inazumi Takashi Washio Shohei Shimizu Joe Suzuki Akihiro Yamamoto Yoshinobu Kawahara
+ PDF Chat	On <i>d</i>-Asymptotics for High-Dimensional Discriminant Analysis with Different Variance-Covariance Matrices	2012	Takanori Ayano Joe Suzuki
+	Discovering causal structures in binary exclusive-or skew acyclic models	2011	Takanori Inazumi Takashi Washio Shohei Shimizu Joe Suzuki Akihiro Yamamoto Yoshinobu Kawahara
+ PDF Chat	A Markov Chain Analysis of Genetic Algorithms: Large Deviation Principle Approach	2010	Joe Suzuki
+ PDF Chat	A Markov Chain Analysis of Genetic Algorithms: Large Deviation Principle Approach	2010	Joe Suzuki
+	Nonparametric Estimation and On-Line Prediction for General Stationary Ergodic Sources	2010	Joe Suzuki
+	The Hannan-Quinn Proposition for Linear Regression	2010	Joe Suzuki
+	A Generalization of the Chow-Liu Algorithm and its Application to Statistical Learning	2010	Joe Suzuki
+	Miura conjecture on Affine curves	2007	Joe Suzuki
+	Generalizing Kedlaya's order counting based on Miura theory	2004	Joe Suzuki
+	Generalizing Kedlaya's order counting based on Miura Theory.	2004	Joe Suzuki
+	Hausdorff dimension as a new dimension in source coding and predicting	2003	Boris Ryabko Joe Suzuki Flemming Topsøe
+	Fast Jacobian Group Arithmetic on C ab Curves	2000	Ryuichi Harasawa Joe Suzuki
+	Optimizing the Menezes-Okamoto-Vanstone (MOV) Algorithm for Non-supersingular Elliptic Curves	1999	Junji Shikata Yuliang Zheng Joe Suzuki Hideki Imai
+ PDF Chat	A Construction of Bayesian Networks from Databases Based on an MDL Principle	1993	Joe Suzuki
+ PDF Chat	$\kappa$-metrizable spaces, stratifiable spaces and metrization	1989	Joe Suzuki Kenichi Tamano Yoshio Tanaka

Common Coauthors

Coauthor	Papers Together
Ryosuke Shimmura	9
Takashi Washio	5
Shohei Shimizu	5
Takanori Inazumi	5
Yoshinobu Kawahara	4
Tian-Le Yang	4
Akihiro Yamamoto	4
Yusuke Inaoka	2
Lirui Liu	2
Kuang‐Yao Lee	2
Jie Chen	1
Kun Zhang	1
Kun Zhang	1
Hideki Imai	1
Yoshio Tanaka	1
Bingyuan Zhang	1
Ryuichi Harasawa	1
Yuliang Zheng	1
Ayano Takanori	1
Flemming Topsøe	1
Kenichi Tamano	1
Boris Ryabko	1
Junji Shikata	1
Jie Chen	1
Takanori Ayano	1
Tian-Le Yang	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	A Construction of Bayesian Networks from Databases Based on an MDL Principle	1993	Joe Suzuki	10
+	A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems	2009	Amir Beck Marc Teboulle	7
+ PDF Chat	Estimating the Dimension of a Model	1978	Gideon Schwarz	7
+ PDF Chat	Model Selection and Estimation in Regression with Grouped Variables	2005	Ming Yuan Yi Lin	6
+	Regression Shrinkage and Selection Via the Lasso	1996	Robert Tibshirani	5
+ PDF Chat	Causal Inference on Discrete Data Using Additive Noise Models	2011	Jonas Peters Dominik Janzing Bernhard Schölkopf	4
+ PDF Chat	A Property of the Normal Distribution	1954	Eugene Lukács E. P. King	3
+ PDF Chat	Sparsity and Smoothness Via the Fused Lasso	2004	Robert Tibshirani Michael A. Saunders Saharon Rosset Ji Zhu Keith Knight	3
+	Robustness of a multivariate normal approximation for imputation of incomplete binary data	2006	Coen Bernaards Thomas R. Belin Joseph L. Schafer	3
+	Elements of information theory	1996	Shu‐Heng Chen	3
+ PDF Chat	A theoretical analysis of the BDeu scores in Bayesian network structure learning	2016	Joe Suzuki	3
+ PDF Chat	Estimating mutual information	2004	Alexander Kraskov Harald Stögbauer Peter Grassberger	3
+	Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing	1995	Yoav Benjamini Yosef Hochberg	3
+ PDF Chat	The Strong Ergodic Theorem for Densities: Generalized Shannon-McMillan-Breiman Theorem	1985	Andrew R. Barron	3
+ PDF Chat	ParceLiNGAM: A Causal Ordering Method Robust Against Latent Confounders	2013	Tatsuya Tashiro Shohei Shimizu Aapo Hyvärinen Takashi Washio	3
+	On the Dirichlet Prior and Bayesian Regularization	2002	Harald Steck Tommi Jaakkola	2
+	Theory of probability	1939	Harold Jeffreys R. Bruce Lindsay	2
+	QUIC: quadratic approximation for sparse inverse covariance estimation	2014	Cho‐Jui Hsieh Mátyás A. Sustik Inderjit S. Dhillon Pradeep Ravikumar	2
+	Learning High-Dimensional Markov Forest Distributions: Analysis of Error Rates	2011	Vincent Y. F. Tan Animashree Anandkumar Alan S. Willsky	2
+	A note on the group lasso and a sparse group lasso	2010	Jerome H. Friedman Trevor Hastie Robert Tibshirani	2
+	Iterative Thresholding Algorithm for Sparse Inverse Covariance Estimation	2012	Dominique Guillot Bala Rajaratnam Benjamin T. Rolfs Arian Maleki Ian Wong	2
+	Sparse inverse covariance estimation with the graphical lasso	2007	Jerome H. Friedman Trevor Hastie R. Tibshirani	2
+ PDF Chat	The graphical lasso: New insights and alternatives	2012	Rahul Mazumder Trevor Hastie	2
+	Iterative Solution of Nonlinear Equations in Several Variables	2000	J. M. Ortega Werner C. Rheinboldt	2
+ PDF Chat	Theory Refinement on Bayesian Networks	1991	Wray Buntine	2
+ PDF Chat	Clusterpath An Algorithm for Clustering using Convex Fusion Penalties	2011	Toby Dylan Hocking Armand Joulin Francis Bach Jean‐Philippe Vert	2
+	Composite self-concordant minimization	2015	Quoc Tran-Dinh Anastasios Kyrillidis Volkan Cevher	2
+ PDF Chat	Fused Multiple Graphical Lasso	2015	Sen Yang Zhaosong Lu Xiaotong Shen Peter Wonka Jieping Ye	2
+ PDF Chat	From Relational Databases to Belief Networks	1991	Wilson X. Wen	2
+	The Determination of the Order of an Autoregression	1979	E. J. Hannan Barry G. Quinn	2
+	Interior-Point Polynomial Algorithms in Convex Programming	1994	Yurii Nesterov Arkadi Nemirovski	2
+	Two-Point Step Size Gradient Methods	1988	Jonathan Barzilai Jonathan M. Borwein	2
+ PDF Chat	Pathwise coordinate optimization	2007	Jerome H. Friedman Trevor Hastie Holger Höfling Robert Tibshirani	2
+	Statistical Analysis With Missing Data	1989	Maureen Lahiff Roderick J. A. Little Donald B. Rubin	2
+	Information Theory and an Extension of the Maximum Likelihood Principle	1998	H. Akaike	2
+	A Remark Concerning m-Divisibility and the Discrete Logarithm in the Divisor Class Group of Curves	1994	Gerhard Frey Hans-Georg Rück	2
+ PDF Chat	Uncertainty in artificial intelligence	1994	Simon Parsons	2
+	A Dynamic Programming Algorithm for the Fused Lasso and<i>L</i><sub>0</sub>-Segmentation	2013	Nicholas A. Johnson	2
+ PDF Chat	On the shortest spanning subtree of a graph and the traveling salesman problem	1956	Joseph B. Kruskal	2
+	Strong consistency of least squares estimates in multiple regression	1978	Tze Leung Lai Herbert Robbins Ching-Zong Wei	2
+ PDF Chat	Smooth Optimization Approach for Sparse Covariance Selection	2009	Zhaosong Lu	2
+	Statistical Learning with Sparsity	2015	Trevor Hastie Robert Tibshirani Martin J. Wainwright	2
+	Proximal Newton methods for convex composite optimization	2013	Panagiotis Patrinos Alberto Bemporad	2
+ PDF Chat	A Path Algorithm for the Fused Lasso Signal Approximator	2010	Hölger Hoefling	2
+	Model selection and estimation in the Gaussian graphical model	2007	Ming Yuan Yi Lin	2
+ PDF Chat	Learning a common substructure of multiple graphical Gaussian models	2012	Satoshi Hara Takashi Washio	2
+	A Course in Computational Algebraic Number Theory	1993	Henri Cohen	2
+ PDF Chat	Exact Hybrid Covariance Thresholding for Joint Graphical Lasso	2015	Qingming Tang Chao Yang Jian Peng Jinbo Xu	2
+ PDF Chat	A Bayesian Method for Constructing Bayesian Belief Networks from Databases	1991	Gregory F. Cooper Edward H. Herskovits	2
+	A direct method for estimating a causal ordering in a linear non-Gaussian acyclic model	2014	Shohei Shimizu Aapo Hyvärinen Yoshinobu Kawahara Takashi Washio	2