2025
Estimation of the Learning Coefficient Using Empirical Loss.
CoRR, February, 2025
2024
Newton-Type Methods with the Proximal Gradient Step for Sparse Estimation.
Oper. Res. Forum, June, 2024
Estimation of a Simple Structure in a Multidimensional IRT Model Using Structure Regularization.
Entropy, January, 2024
An Efficient Procedure for Computing Bayesian Network Structure Learning.
CoRR, 2024
Learning under Singularity: An Information Criterion improving WBIC and sBIC.
CoRR, 2024
Functional Linear Non-Gaussian Acyclic Model for Causal Discovery.
CoRR, 2024
Generalization of LiNGAM that Allows Confounding.
Proceedings of the IEEE International Symposium on Information Theory, 2024
2023
Extending Hilbert-Schmidt Independence Criterion for Testing Conditional Independence.
Entropy, March, 2023
Dropout Drops Double Descent.
CoRR, 2023
WAIC and WBIC with R Stan - 100 Exercises for Building Logic
Springer, ISBN: 978-981-99-3837-7, 2023
2022
Proceedings of the International Conference on Probabilistic Graphical Models, 2022
Kernel Methods for Machine Learning with Math and R - 100 Exercises for Building Logic
Springer, ISBN: 978-981-19-0397-7, 2022
2021
Efficient Proximal Gradient Algorithms for Joint Graphical Lasso.
Entropy, 2021
Causal Order Identification to Address Confounding: Binary Variables.
CoRR, 2021
Sparse Estimation with Math and R - 100 Exercises for Building Logic
Springer, ISBN: 978-981-16-1445-3, 2021
2020
Statistical Learning with Math and R - 100 Exercises for Building Logic
Springer, ISBN: 978-981-15-7567-9, 2020
2019
Mutual Information Estimation: Independence Detection and Consistency.
Proceedings of the IEEE International Symposium on Information Theory, 2019
2018
Forest Learning From Data and its Universal Coding.
IEEE Trans. Inf. Theory, 2018
2017
An Efficient Bayesian Network Structure Learning Strategy.
New Gener. Comput., 2017
A novel Chow-Liu algorithm and its application to gene differential analysis.
Int. J. Approx. Reason., 2017
Branch and Bound for Regular Bayesian Network Structure Learing.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017
Advanced Methodologies for Bayesian Networks 2017: Preface.
Proceedings of the 3rd Workshop on Advanced Methodologies for Bayesian Networks, 2017
2016
An Estimator of Mutual Information and its Application to Independence Testing.
Entropy, 2016
A Theoretical Analysis of the BDeu Scores in Bayesian Network Structure Learning.
CoRR, 2016
Structure learning and universal coding when missing values exist.
Proceedings of the IEEE International Symposium on Information Theory, 2016
2015
Consistency of Learning Bayesian Network Structures with Continuous Variables: An Information Theoretic Approach.
Entropy, 2015
Forest Learning Based on the Chow-Liu Algorithm and Its Application to Genome Differential Analysis: A Novel Mutual Information Estimation.
Proceedings of the Advanced Methodologies for Bayesian Networks, 2015
Efficiently Learning Bayesian Network Structures Based on the B&B Strategy: A Theoretical Analysis.
Proceedings of the Advanced Methodologies for Bayesian Networks, 2015
2014
Universal Bayesian Measures and Universal Histogram Sequences.
CoRR, 2014
Causal Discovery in a Binary Exclusive-or Skew Acyclic Model: BExSAM.
CoRR, 2014
Learning Bayesian Network Structures When Discrete and Continuous Variables Are Present.
Proceedings of the Probabilistic Graphical Models - 7th European Workshop, 2014
2013
Universal Bayesian measures.
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.
IEICE Trans. Inf. Syst., 2012
Bayesian criteria based on universal measures.
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.
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.
Proceedings of the UAI 2011, 2011
The Universal Measure for General Sources and Its Application to MDL/Bayesian Criteria.
Proceedings of the 2011 Data Compression Conference (DCC 2011), 2011
MDL/Bayesian Criteria Based on Universal Coding/Measure.
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
CoRR, 2010
A Generalization of the Chow-Liu Algorithm and its Application to Statistical Learning
CoRR, 2010
A Generalization of the Chow-Liu Algorithm and its Application to Artificial Intelligence.
Proceedings of the 2010 International Conference on Artificial Intelligence, 2010
2006
On Strong Consistency of Model Selection in Classification.
IEEE Trans. Inf. Theory, 2006
2005
On the stationary distribution of GAs with fixed crossover probability.
Proceedings of the Genetic and Evolutionary Computation Conference, 2005
2004
Coding combinatorial sources with costs.
IEEE Trans. Inf. Theory, 2004
Generalizing Kedlaya's order counting based on Miura Theory.
IACR Cryptol. ePrint Arch., 2004
2003
Universal prediction and universal coding.
Syst. Comput. Jpn., 2003
2000
Fast Jacobian Group Arithmetic on <i>C<sub>ab</sub></i>Curves.
Proceedings of the Algorithmic Number Theory, 4th International Symposium, 2000
1999
Comparing the MOV and FR Reductions in Elliptic Curve Cryptography.
Proceedings of the Advances in Cryptology, 1999
Optimizing the Menezes-Okamoto-Vanstone (MOV) Algorithm for Non-supersingular Elliptic Curves.
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.
IEEE Trans. Syst. Man Cybern. Part B, 1998
Elliptic Curve Discrete Logarithms and the Index Calculus.
Proceedings of the Advances in Cryptology, 1998
1997
On the Error Probability of Model Selection for Classification.
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.
Proceedings of the Machine Learning, 1996
A CTW Scheme for Non-Tree Sources.
Proceedings of the 6th Data Compression Conference (DCC '96), Snowbird, Utah, USA, March 31, 1996
1995
A Markov chain analysis on simple genetic algorithms.
IEEE Trans. Syst. Man Cybern., 1995
1993
A Construction of Bayesian Networks from Databases Based on an MDL Principle.
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.
Proceedings of the 5th International Conference on Genetic Algorithms, 1993