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Joe Suzuki

Orcid: 0000-0002-3195-9922

According to our database1, Joe Suzuki authored at least 56 papers between 1993 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
Newton-Type Methods with the Proximal Gradient Step for Sparse Estimation.
[BibTeX]
[DOI]
Ryosuke Shimmura
,
Joe Suzuki
Oper. Res. Forum, June, 2024

Estimation of a Simple Structure in a Multidimensional IRT Model Using Structure Regularization.
[BibTeX]
[DOI]
Ryosuke Shimmura
,
Joe Suzuki
Entropy, January, 2024

An Efficient Procedure for Computing Bayesian Network Structure Learning.
[BibTeX]
[DOI]
Hongming Huang
,
Joe Suzuki
CoRR, 2024

Learning under Singularity: An Information Criterion improving WBIC and sBIC.
[BibTeX]
[DOI]
Lirui Liu
,
Joe Suzuki
CoRR, 2024

Functional Linear Non-Gaussian Acyclic Model for Causal Discovery.
[BibTeX]
[DOI]
Tianle Yang
,
Kuang-Yao Lee
,
Kun Zhang
,
Joe Suzuki
CoRR, 2024

Generalization of LiNGAM that Allows Confounding.
[BibTeX]
[DOI]
Joe Suzuki
,
Tianle Yang
Proceedings of the IEEE International Symposium on Information Theory, 2024

2023
Extending Hilbert-Schmidt Independence Criterion for Testing Conditional Independence.
[BibTeX]
[DOI]
Bingyuan Zhang
,
Joe Suzuki
Entropy, March, 2023

Dropout Drops Double Descent.
[BibTeX]
[DOI]
Tianle Yang
,
Joe Suzuki
CoRR, 2023

WAIC and WBIC with R Stan - 100 Exercises for Building Logic
[BibTeX]
[DOI]
Joe Suzuki
Springer, ISBN: 978-981-99-3837-7, 2023

2022
The Functional LiNGAM.
[BibTeX]
[DOI]
Tianle Yang
,
Joe Suzuki
Proceedings of the International Conference on Probabilistic Graphical Models, 2022

Kernel Methods for Machine Learning with Math and R - 100 Exercises for Building Logic
[BibTeX]
[DOI]
Joe Suzuki
Springer, ISBN: 978-981-19-0397-7, 2022

2021
Efficient Proximal Gradient Algorithms for Joint Graphical Lasso.
[BibTeX]
[DOI]
Jie Chen
,
Ryosuke Shimmura
,
Joe Suzuki
Entropy, 2021

Causal Order Identification to Address Confounding: Binary Variables.
[BibTeX]
[DOI]
Joe Suzuki
,
Yusuke Inaoka
CoRR, 2021

Sparse Estimation with Math and R - 100 Exercises for Building Logic
[BibTeX]
[DOI]
Joe Suzuki
Springer, ISBN: 978-981-16-1445-3, 2021

2020
Statistical Learning with Math and R - 100 Exercises for Building Logic
[BibTeX]
[DOI]
Joe Suzuki
Springer, ISBN: 978-981-15-7567-9, 2020

2019
Mutual Information Estimation: Independence Detection and Consistency.
[BibTeX]
[DOI]
Joe Suzuki
Proceedings of the IEEE International Symposium on Information Theory, 2019

2018
Forest Learning From Data and its Universal Coding.
[BibTeX]
[DOI]
Joe Suzuki
IEEE Trans. Inf. Theory, 2018

2017
An Efficient Bayesian Network Structure Learning Strategy.
[BibTeX]
[DOI]
Joe Suzuki
New Gener. Comput., 2017

A novel Chow-Liu algorithm and its application to gene differential analysis.
[BibTeX]
[DOI]
Joe Suzuki
Int. J. Approx. Reason., 2017

Branch and Bound for Regular Bayesian Network Structure Learing.
[BibTeX]
[DOI]
Joe Suzuki
,
Jun Kawahara
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

Advanced Methodologies for Bayesian Networks 2017: Preface.
[BibTeX]
[DOI]
Joe Suzuki
,
Antti Hyttinen
,
Brandon M. Malone
Proceedings of the 3rd Workshop on Advanced Methodologies for Bayesian Networks, 2017

2016
An Estimator of Mutual Information and its Application to Independence Testing.
[BibTeX]
[DOI]
Joe Suzuki
Entropy, 2016

A Theoretical Analysis of the BDeu Scores in Bayesian Network Structure Learning.
[BibTeX]
[DOI]
Joe Suzuki
CoRR, 2016

Structure learning and universal coding when missing values exist.
[BibTeX]
[DOI]
Joe Suzuki
Proceedings of the IEEE International Symposium on Information Theory, 2016

2015
Consistency of Learning Bayesian Network Structures with Continuous Variables: An Information Theoretic Approach.
[BibTeX]
[DOI]
Joe Suzuki
Entropy, 2015

Forest Learning Based on the Chow-Liu Algorithm and Its Application to Genome Differential Analysis: A Novel Mutual Information Estimation.
[BibTeX]
[DOI]
Joe Suzuki
Proceedings of the Advanced Methodologies for Bayesian Networks, 2015

Efficiently Learning Bayesian Network Structures Based on the B&B Strategy: A Theoretical Analysis.
[BibTeX]
[DOI]
Joe Suzuki
Proceedings of the Advanced Methodologies for Bayesian Networks, 2015

2014
Universal Bayesian Measures and Universal Histogram Sequences.
[BibTeX]
[DOI]
Joe Suzuki
CoRR, 2014

Causal Discovery in a Binary Exclusive-or Skew Acyclic Model: BExSAM.
[BibTeX]
[DOI]
Takanori Inazumi
,
Takashi Washio
,
Shohei Shimizu
,
Joe Suzuki
,
Akihiro Yamamoto
,
Yoshinobu Kawahara
CoRR, 2014

Learning Bayesian Network Structures When Discrete and Continuous Variables Are Present.
[BibTeX]
[DOI]
Joe Suzuki
Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014

2013
Universal Bayesian measures.
[BibTeX]
[DOI]
Joe Suzuki
Proceedings of the 2013 IEEE International Symposium on Information Theory, 2013

2012
On <i>d</i>-Asymptotics for High-Dimensional Discriminant Analysis with Different Variance-Covariance Matrices.
[BibTeX]
[DOI]
Takanori Ayano
,
Joe Suzuki
IEICE Trans. Inf. Syst., 2012

Bayesian criteria based on universal measures.
[BibTeX]
[DOI]
Joe Suzuki
Proceedings of the International Symposium on Information Theory and its Applications, 2012

Bayesian Network Structure Estimation Based on the Bayesian/MDL Criteria When Both Discrete and Continuous Variables Are Present.
[BibTeX]
[DOI]
Joe Suzuki
Proceedings of the 2012 Data Compression Conference, Snowbird, UT, USA, April 10-12, 2012, 2012

2011
Discovering causal structures in binary exclusive-or skew acyclic models.
[BibTeX]
[DOI]
Takanori Inazumi
,
Takashi Washio
,
Shohei Shimizu
,
Joe Suzuki
,
Akihiro Yamamoto
,
Yoshinobu Kawahara
Proceedings of the UAI 2011, 2011

The Universal Measure for General Sources and Its Application to MDL/Bayesian Criteria.
[BibTeX]
[DOI]
Joe Suzuki
Proceedings of the 2011 Data Compression Conference (DCC 2011), 2011

MDL/Bayesian Criteria Based on Universal Coding/Measure.
[BibTeX]
[DOI]
Joe Suzuki
Proceedings of the Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence, 2011

2010
Nonparametric Estimation and On-Line Prediction for General Stationary Ergodic Sources
[BibTeX]
[DOI]
Joe Suzuki
CoRR, 2010

A Generalization of the Chow-Liu Algorithm and its Application to Statistical Learning
[BibTeX]
[DOI]
Joe Suzuki
CoRR, 2010

A Generalization of the Chow-Liu Algorithm and its Application to Artificial Intelligence.
[BibTeX]
Joe Suzuki
Proceedings of the 2010 International Conference on Artificial Intelligence, 2010

2006
On Strong Consistency of Model Selection in Classification.
[BibTeX]
[DOI]
Joe Suzuki
IEEE Trans. Inf. Theory, 2006

2005
On the stationary distribution of GAs with fixed crossover probability.
[BibTeX]
[DOI]
U. Chandimal de Silva
,
Joe Suzuki
Proceedings of the Genetic and Evolutionary Computation Conference, 2005

2004
Coding combinatorial sources with costs.
[BibTeX]
[DOI]
Joe Suzuki
,
Boris Ryabko
IEEE Trans. Inf. Theory, 2004

Generalizing Kedlaya's order counting based on Miura Theory.
[BibTeX]
[DOI]
Joe Suzuki
IACR Cryptol. ePrint Arch., 2004

2003
Universal prediction and universal coding.
[BibTeX]
[DOI]
Joe Suzuki
Syst. Comput. Jpn., 2003

2000
Fast Jacobian Group Arithmetic on <i>C<sub>ab</sub></i>Curves.
[BibTeX]
[DOI]
Ryuichi Harasawa
,
Joe Suzuki
Proceedings of the Algorithmic Number Theory, 4th International Symposium, 2000

1999
Comparing the MOV and FR Reductions in Elliptic Curve Cryptography.
[BibTeX]
[DOI]
Ryuichi Harasawa
,
Junji Shikata
,
Joe Suzuki
,
Hideki Imai
Proceedings of the Advances in Cryptology, 1999

Optimizing the Menezes-Okamoto-Vanstone (MOV) Algorithm for Non-supersingular Elliptic Curves.
[BibTeX]
[DOI]
Junji Shikata
,
Yuliang Zheng
,
Joe Suzuki
,
Hideki Imai
Proceedings of the Advances in Cryptology, 1999

1998
A further result on the Markov chain model of genetic algorithms and its application to a simulated annealing-like strategy.
[BibTeX]
[DOI]
Joe Suzuki
IEEE Trans. Syst. Man Cybern. Part B, 1998

Elliptic Curve Discrete Logarithms and the Index Calculus.
[BibTeX]
[DOI]
Joseph H. Silverman
,
Joe Suzuki
Proceedings of the Advances in Cryptology, 1998

1997
On the Error Probability of Model Selection for Classification.
[BibTeX]
[DOI]
Joe Suzuki
Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, 1997

1996
Learning Bayesian Belief Networks Based on the Minimum Description Length Principle: An Efficient Algorithm Using the B & B Technique.
[BibTeX]
Joe Suzuki
Proceedings of the Machine Learning, 1996

A CTW Scheme for Non-Tree Sources.
[BibTeX]
[DOI]
Joe Suzuki
Proceedings of the 6th Data Compression Conference (DCC '96), Snowbird, Utah, USA, March 31, 1996

1995
A Markov chain analysis on simple genetic algorithms.
[BibTeX]
[DOI]
Joe Suzuki
IEEE Trans. Syst. Man Cybern., 1995

1993
A Construction of Bayesian Networks from Databases Based on an MDL Principle.
[BibTeX]
[DOI]
Joe Suzuki
Proceedings of the UAI '93: Proceedings of the Ninth Annual Conference on Uncertainty in Artificial Intelligence, 1993

A Markov Chain Analysis on A Genetic Algorithm.
[BibTeX]
Joe Suzuki
Proceedings of the 5th International Conference on Genetic Algorithms, 1993


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