Publications & Awards

2024

Conference Neural Tangent Kernels for Axis-Aligned Tree Ensembles
Kanoh, R., Sugiyama, M. The 41st International Conference on Machine Learning (ICML 2024), 2024.
[BibTeX] [Paper] [Poster] [Code]
Conference Bringing Structure to Naturalness: On the Naturalness of ASTs
Pârțachi, P.-P., Sugiyama, M. 46th International Conference on Software Engineering (ICSE 2024), Posters Track, 2024.
[BibTeX] [Paper] [DOI: 10.1145/3639478.3643517]
Review Primer on Graph Machine Learning
Yamada, M., Sugiyama, M. Drug Development Supported by Informatics, Springer, 87–102, 2024.
[BibTeX] [Paper]
Review Subgraph-Based Molecular Graph Generation
Yamada, M., Sugiyama, M. Drug Development Supported by Informatics, Springer, 103–119, 2024.
[BibTeX] [Paper]

2023

Journal Unsupervised Tensor Based Feature Extraction from Multivariate Time Series
Matsue, K., Sugiyama, M. IEEE Access, 2023.
[BibTeX] [DOI: 10.1109/ACCESS.2023.3326073]
Journal How Graph Features from Message Passing Affect Graph Classification and Regression?
Yamada, M., Sugiyama, M. Intelligent Data Analysis, 2023. (in press)
[BibTeX] [DOI: 10.3233/IDA-227190]
Journal Molecular Graph Generation by Decomposition and Reassembling
Yamada, M., Sugiyama, M. ACS Omega, 2023.
[BibTeX] [arXiv] [DOI: 10.1021/acsomega.3c01078]
Journal Artificial Neural Network Encoding of Molecular Wavefunctions for Quantum Computing
Hagai, M., Sugiyama, M., Tsuda, K., Yanai, T. Digital Discovery, 2023.
[BibTeX] [Paper] [DOI: 10.1039/d2dd00093h]
Journal Non-negative Low-rank Approximations for Multi-dimensional Arrays on Statistical Manifold
Ghalamkari, K., Sugiyama, M. Information Geometry, 2023.
[BibTeX] [Paper] [DOI: 10.1007/s41884-023-00100-5]
Conference Many-body Approximation for Non-negative Tensors
Ghalamkari, K., Sugiyama, M., Kawahara, Y. Advances in Neural Information Processing Systems (NeurIPS 2023), 2023.
[BibTeX] [arXiv] [OpenReview] [Poster]
Conference Analyzing Tree Architectures in Ensembles via Neural Tangent Kernel
Kanoh, R., Sugiyama, M. The 11th International Conference on Learning Representations (ICLR 2023), 2023.
[BibTeX] [arXiv] [OpenReview] [Poster]
Workshop Energy-Based Non-Negative Tensor Factorization via Multi-Body Modeling
Ghalamkari, K., Sugiyama, M. ICML 2023 Workshop Duality Principles for Modern Machine Learning, 2023.
Workshop Investigating Axis-Aligned Differentiable Trees through Neural Tangent Kernels
Kanoh, R., Sugiyama, M. ICML 2023 Workshop Differentiable Almost Everything, 2023.
Award 2023 JSAI Annual Conference Award
Ghalamkari, K., Sugiyama, M.
Award 2023 JSAI Annual Conference Award
Kanoh, R., Sugiyama, M.

2022

Journal A Drive-by Bridge Inspection Framework Using Non-Parametric Clusters over Projected Data Manifolds
Cheema, P., Makki Alamdari, M., Chang, K. C., Kim, C. W., Sugiyama, M. Mechanical Systems and Signal Processing (MSSP), 2022.
[BibTeX] [Paper] [DOI: 10.1016/j.ymssp.2022.109401]
Conference A Neural Tangent Kernel Perspective of Infinite Tree Ensembles
Kanoh, R., Sugiyama, M. The 10th International Conference on Learning Representations (ICLR 2022), 2022.
[BibTeX] [arXiv] [OpenReview] [Poster]
Conference Fast Rank-1 NMF for Missing Data with KL Divergence
Ghalamkari, K., Sugiyama, M. The 25th International Conference on Artificial Intelligence and Statistics (AISTATS 2022), 2022.
[BibTeX] [Paper] [arXiv] [Code] [Poster]

2021

Journal Unsupervised Feature Extraction from Multivariate Time Series for Outlier Detection
Matsue, K., Sugiyama, M. Intelligent Data Analysis, 2021.
[BibTeX] [Paper] [DOI: 10.3233/IDA-216128]
Conference Fast Tucker Rank Reduction for Non-Negative Tensors Using Mean-Field Approximation
Ghalamkari, K., Sugiyama, M. Advances in Neural Information Processing Systems (NeurIPS 2021), 2021.
[BibTeX] [arXiv] [Paper] [Code] [Slide] [Poster]
Conference Investigating Overparameterization for Non-Negative Matrix Factorization in Collaborative Filtering
Kawakami, Y., Sugiyama, M. The 15th ACM Conference on Recommender Systems (RecSys 2021), Late-Breaking Results track, 2021.
[BibTeX] [Paper] [DOI: 10.1145/3460231.3478854]
Conference Unsupervised Tensor based Feature Extraction and Outlier Detection for Multivariate Time Series
Matsue, K., Sugiyama, M. The 8th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2021), 2021.
[BibTeX] [Paper] [Code] [DOI: 10.1109/DSAA53316.2021.9564117]
Conference Job Recommendation with Career Graphs
Tanida, H., Sugiyama, M., Shikauchi, M., Oba, S. The 8th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2021), Industrial Track, 2021.
[BibTeX]
Conference Hierarchical Probabilistic Model for Blind Source Separation via Legendre Transformation
Luo, S., Azizi, L., Sugiyama, M. The 37th Conference on Uncertainty in Artificial Intelligence (UAI 2021), 2021.
[BibTeX] [arXiv] [Paper]
Award 2021 JSAI Incentive Award
Kanoh, R., Sugiyama, M.
Award 2021 JSAI Annual Conference Award
Ghalamkari, K., Sugiyama, M.

2020

Journal Artificial Neural Networks Applied as Molecular Wave Function Solvers
Peng-Jian, Y., Sugiyama, M., Tsuda, K., Yanai, T. Journal of Chemical Theory and Computation, 2020.
[BibTeX] [DOI: 10.1021/acs.jctc.9b01132]
Conference Testing Machine Learning Code using Polyhedral Region
Ahmed, M. S., Ishikawa, F., Sugiyama, M. The 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2020), Visions and Reflections Track, 2020.
[BibTeX] [Paper] [DOI: 10.1145/3368089.3417043]
Conference Coordinate Descent Method for Log-Linear Model on Posets
Hayashi, S., Sugiyama, M., Matsushima, S. The 7th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2020), 2020.
[BibTeX] [DOI: 10.1109/DSAA49011.2020.00022]
Workshop Unintended Effects on Adaptive Learning Rate for Training Neural Network with Output Scale Change
Kanoh, R., Sugiyama, M. NeurIPS 2020 Workshop: Beyond BackPropagation, 2020.
[BibTeX]
Workshop Convex Optimization for Blind Source Separation on Statistical Manifolds
Luo, S., Azizi, L., Sugiyama, M. NeurIPS 2020 Workshop: Differential Geometry meets Deep Learning, 2020.
[BibTeX]
Workshop Towards Geometric Understanding of Low-Rank Approximation
Ghalamkari, K., Sugiyama, M. NeurIPS 2020 Workshop: Differential Geometry meets Deep Learning, 2020.
[BibTeX]
Workshop Sample Space Truncation on Boltzmann Machines
Sugiyama, M., Tsuda, K., Nakahara, H. NeurIPS 2020 Workshop: Deep Learning through Information Geometry, 2020.
[BibTeX]
Workshop The Volume of Non-Restricted Boltzmann Machines and Their Double Descent Model Complexity
Cheema, P., Sugiyama, M. NeurIPS 2020 Workshop: Deep Learning through Information Geometry, 2020.
Award (This paper won the best paper award)
[BibTeX]
Workshop Learning Joint Intensity in a Multivariate Poisson Process on Statistical Manifolds
Luo, S., Zhou, F., Azizi, L., Sugiyama, M. NeurIPS 2020 Workshop: Deep Learning through Information Geometry, 2020.
[BibTeX]
Workshop A Deep Architecture for Log-Linear Models
Luo, S., Cripps, S., Sugiyama, M. NeurIPS 2020 Workshop: Deep Learning through Information Geometry, 2020.
[BibTeX]

2019

Journal Legendre Decomposition for Tensors
Sugiyama, M., Nakahara, H., Tsuda, K. Journal of Statistical Mechanics: Theory and Experiment, 2019.
[BibTeX] [Paper] [DOI: 10.1088/1742-5468/ab3196]
Journal Summarizing Significant Subgraphs by Probabilistic Logic Programming
Bellodi, E., Sato, K., Sugiyama, M. Intelligent Data Analysis, 2019.
[BibTeX] [DOI: 10.3233/IDA-184339]
Conference Finding Statistically Significant Interactions between Continuous Features
Sugiyama, M., Borgwardt, K.M. The 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), 2019.
[BibTeX] [arXiv] [Paper] [Code] [Slide] [Poster] [DOI: 10.24963/ijcai.2019/484]
Conference Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions
Luo, S., Sugiyama, M. The 33rd AAAI Conference on Artificial Intelligence (AAAI-19), 2019.
[BibTeX] [arXiv] [Paper] [Code] [DOI: 10.1609/aaai.v33i01.33014488]

2018

Journal graphkernels: R and Python Packages for Graph Comparison
Sugiyama, M., Ghisu, E., Llinares-López, F., Borgwardt, K.M. Bioinformatics, 34(3), 530—532, 2018
[BibTeX] [Paper] [Library (R)] [Library (Python)] [DOI: 10.1093/bioinformatics/btx602]
Conference Legendre Decomposition for Tensors
Sugiyama, M., Nakahara, H., Tsuda, K. Advances in Neural Information Processing Systems (NeurIPS2018), 2018.
[BibTeX] [arXiv] [Paper] [Code] [Slide] [Poster] [Video]
Workshop Learning Graph Representation via Formal Concept Analysis
Yoneda, Y., Sugiyama, M., Washio, T. NeurIPS 2018 Workshop on Relational Representation Learning, 2018.
[BibTeX] [arXiv]
Award 2018 JSAI Incentive Award
Yoneda, Y., Sugiyama, M., Washio, T.

2017

Conference Tensor Balancing on Statistical Manifold
Sugiyama, M., Nakahara, H., Tsuda, K. The 34th International Conference on Machine Learning (ICML 2017), 2017.
[BibTeX] [arXiv] [Paper] [Code] [Slide] [Poster] [Video]
Review Searching for Bacterial Pathogens in the Digital Ocean—Executive Summary
Giuliano, L., Dorman, C., Bowler, C., Sugiyama, M., Vezzulli, L., Czerucka, D., Le Roux, F., D'Auria, G., Troussellier, M., Briand, F. CIESM Workshop Monograph, 49, 5–25, 2017.
[BibTeX] [Paper]
Review Finding Statistically Significant Patterns from Data
Sugiyama, M. CIESM Workshop Monograph, 49, 53–58, 2017.
[BibTeX]
Review Pattern Mining with Statistical Significance (in Japanese)
Sugiyama, M. Communications of the Operations Research Society of Japan, 62(4), 226–232, 2017.
[BibTeX] [Paper]
Award 2017 JSAI Incentive Award
Sugiyama, M., Nakahara, H., Tsuda, K.