Joe Suzuki - RankMe

64 papers A* 2A 8B 7C 1Misc 1Journal 31Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Estimation of the Learning Coefficient Using Empirical Loss. CoRR Tatsuyoshi Takio, Joe Suzuki
2024	J	`jnl`	An Efficient Procedure for Computing Bayesian Network Structure Learning. CoRR Hongming Huang, Joe Suzuki
2024	J	`jnl`	Estimation of a Simple Structure in a Multidimensional IRT Model Using Structure Regularization. Entropy Ryosuke Shimmura, Joe Suzuki
2024	J	`jnl`	Functional Linear Non-Gaussian Acyclic Model for Causal Discovery. CoRR Tianle Yang, Kuang-Yao Lee, Kun Zhang, Joe Suzuki
2024	B	`conf`	Generalization of LiNGAM that Allows Confounding. ISIT Joe Suzuki, Tianle Yang
2024	J	`jnl`	Generalization of LiNGAM that allows confounding. CoRR Joe Suzuki, Tianle Yang
2024	J	`jnl`	Learning under Singularity: An Information Criterion improving WBIC and sBIC. CoRR Lirui Liu, Joe Suzuki
2024	J	`jnl`	Newton-Type Methods with the Proximal Gradient Step for Sparse Estimation. Oper. Res. Forum Ryosuke Shimmura, Joe Suzuki
2023	J	`jnl`	Dropout Drops Double Descent. CoRR Tianle Yang, Joe Suzuki
2023	J	`jnl`	Extending Hilbert-Schmidt Independence Criterion for Testing Conditional Independence. Entropy Bingyuan Zhang, Joe Suzuki
2023	—	`book`	WAIC and WBIC with R Stan - 100 Exercises for Building Logic Joe Suzuki
2022	—	`book`	Kernel Methods for Machine Learning with Math and R - 100 Exercises for Building Logic Joe Suzuki
2022	—	`conf`	The Functional LiNGAM. PGM Tianle Yang, Joe Suzuki
2021	J	`jnl`	Causal Order Identification to Address Confounding: Binary Variables. CoRR Joe Suzuki, Yusuke Inaoka
2021	J	`jnl`	Efficient Proximal Gradient Algorithms for Joint Graphical Lasso. Entropy Jie Chen, Ryosuke Shimmura, Joe Suzuki
2021	—	`book`	Sparse Estimation with Math and R - 100 Exercises for Building Logic Joe Suzuki
2020	—	`book`	Statistical Learning with Math and R - 100 Exercises for Building Logic Joe Suzuki
2019	B	`conf`	Mutual Information Estimation: Independence Detection and Consistency. ISIT Joe Suzuki
2018	J	`jnl`	Forest Learning From Data and its Universal Coding. IEEE Trans. Inf. Theory Joe Suzuki
2018	J	`jnl`	Forest Learning from Data and its Universal Coding. CoRR Joe Suzuki
2017	J	`jnl`	A novel Chow-Liu algorithm and its application to gene differential analysis. Int. J. Approx. Reason. Joe Suzuki
2017	—	`conf`	Advanced Methodologies for Bayesian Networks 2017: Preface. AMBN Joe Suzuki, Antti Hyttinen, Brandon M. Malone
2017	J	`jnl`	An Efficient Bayesian Network Structure Learning Strategy. New Gener. Comput. Joe Suzuki
2017	A	`conf`	Branch and Bound for Regular Bayesian Network Structure Learing. UAI Joe Suzuki, Jun Kawahara
2017	—	`ed.`	Proceedings of the 3rd Workshop on Advanced Methodologies for Bayesian Networks, AMBN 2017, Kyoto, Japan, September 20-22, 2017 AMBN Antti Hyttinen, Joe Suzuki, Brandon M. Malone
2016	J	`jnl`	A Theoretical Analysis of the BDeu Scores in Bayesian Network Structure Learning. CoRR Joe Suzuki
2016	J	`jnl`	An Estimator of Mutual Information and its Application to Independence Testing. Entropy Joe Suzuki
2016	B	`conf`	Structure learning and universal coding when missing values exist. ISIT Joe Suzuki
2015	—	`ed.`	Advanced Methodologies for Bayesian Networks - Second International Workshop, AMBN 2015, Yokohama, Japan, November 16-18, 2015. Proceedings AMBN@JSAI-isAI Joe Suzuki, Maomi Ueno
2015	J	`jnl`	Consistency of Learning Bayesian Network Structures with Continuous Variables: An Information Theoretic Approach. Entropy Joe Suzuki
2015	—	`conf`	Efficiently Learning Bayesian Network Structures Based on the B&B Strategy: A Theoretical Analysis. AMBN@JSAI-isAI Joe Suzuki
2015	—	`conf`	Forest Learning Based on the Chow-Liu Algorithm and Its Application to Genome Differential Analysis: A Novel Mutual Information Estimation. AMBN@JSAI-isAI Joe Suzuki
2014	J	`jnl`	Causal Discovery in a Binary Exclusive-or Skew Acyclic Model: BExSAM. CoRR Takanori Inazumi, Takashi Washio, Shohei Shimizu, Joe Suzuki, Akihiro Yamamoto, Yoshinobu Kawahara
2014	—	`conf`	Learning Bayesian Network Structures When Discrete and Continuous Variables Are Present. Probabilistic Graphical Models Joe Suzuki
2014	J	`jnl`	Universal Bayesian Measures and Universal Histogram Sequences. CoRR Joe Suzuki
2013	J	`jnl`	A Construction of Bayesian Networks from Databases Based on an MDL Principle CoRR Joe Suzuki
2013	B	`conf`	Universal Bayesian measures. ISIT Joe Suzuki
2012	B	`conf`	Bayesian Network Structure Estimation Based on the Bayesian/MDL Criteria When Both Discrete and Continuous Variables Are Present. DCC Joe Suzuki
2012	C	`conf`	Bayesian criteria based on universal measures. ISITA Joe Suzuki
2012	J	`jnl`	Discovering causal structures in binary exclusive-or skew acyclic models CoRR Takanori Inazumi, Takashi Washio, Shohei Shimizu, Joe Suzuki, Akihiro Yamamoto, Yoshinobu Kawahara
2012	J	`jnl`	On IEICE Trans. Inf. Syst. Takanori Ayano, Joe Suzuki
2011	A	`conf`	Discovering causal structures in binary exclusive-or skew acyclic models. UAI Takanori Inazumi, Takashi Washio, Shohei Shimizu, Joe Suzuki, Akihiro Yamamoto, Yoshinobu Kawahara
2011	—	`conf`	MDL/Bayesian Criteria Based on Universal Coding/Measure. Algorithmic Probability and Friends Joe Suzuki
2011	B	`conf`	The Universal Measure for General Sources and Its Application to MDL/Bayesian Criteria. DCC Joe Suzuki
2010	Misc	`conf`	A Generalization of the Chow-Liu Algorithm and its Application to Artificial Intelligence. IC-AI Joe Suzuki
2010	J	`jnl`	A Generalization of the Chow-Liu Algorithm and its Application to Statistical Learning CoRR Joe Suzuki
2010	J	`jnl`	Nonparametric Estimation and On-Line Prediction for General Stationary Ergodic Sources CoRR Joe Suzuki
2006	J	`jnl`	On Strong Consistency of Model Selection in Classification. IEEE Trans. Inf. Theory Joe Suzuki
2005	A	`conf`	On the stationary distribution of GAs with fixed crossover probability. GECCO U. Chandimal de Silva, Joe Suzuki
2004	J	`jnl`	Coding combinatorial sources with costs. IEEE Trans. Inf. Theory Joe Suzuki, Boris Ryabko
2004	J	`jnl`	Generalizing Kedlaya's order counting based on Miura Theory. IACR Cryptol. ePrint Arch. Joe Suzuki
2003	J	`jnl`	Universal prediction and universal coding. Syst. Comput. Jpn. Joe Suzuki
2000	—	`conf`	Fast Jacobian Group Arithmetic on ANTS Ryuichi Harasawa, Joe Suzuki
1999	A*	`conf`	Comparing the MOV and FR Reductions in Elliptic Curve Cryptography. EUROCRYPT Ryuichi Harasawa, Junji Shikata, Joe Suzuki, Hideki Imai
1999	A	`conf`	Optimizing the Menezes-Okamoto-Vanstone (MOV) Algorithm for Non-supersingular Elliptic Curves. ASIACRYPT Junji Shikata, Yuliang Zheng, Joe Suzuki, Hideki Imai
1998	J	`jnl`	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 Joe Suzuki
1998	A	`conf`	Elliptic Curve Discrete Logarithms and the Index Calculus. ASIACRYPT Joseph H. Silverman, Joe Suzuki
1997	A	`conf`	On the Error Probability of Model Selection for Classification. AISTATS Joe Suzuki
1996	B	`conf`	A CTW Scheme for Non-Tree Sources. Data Compression Conference Joe Suzuki
1996	A	`conf`	A Further Result on the Markov Chain Model of Genetic Algorithms and Its Application to a Simulated Annealing-like Strategy. FOGA Joe Suzuki
1996	A*	`conf`	Learning Bayesian Belief Networks Based on the Minimum Description Length Principle: An Efficient Algorithm Using the B & B Technique. ICML Joe Suzuki
1995	J	`jnl`	A Markov chain analysis on simple genetic algorithms. IEEE Trans. Syst. Man Cybern. Joe Suzuki
1993	A	`conf`	A Construction of Bayesian Networks from Databases Based on an MDL Principle. UAI Joe Suzuki
1993	—	`conf`	A Markov Chain Analysis on A Genetic Algorithm. ICGA Joe Suzuki