Mahito Sugiyama

74 papers A* 13A 6B 4C 1Misc 1Journal 41Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Complete Decomposition of KL Error using Refined Information and Mode Interaction Selection. Trans. Mach. Learn. Res. James Enouen, Mahito Sugiyama
2026	J	`jnl`	Quadratic polarity and polar Fenchel-Young divergences from the canonical Legendre polarity. CoRR Frank Nielsen, Basile Plus-Gourdon, Mahito Sugiyama
2025	J	`jnl`	Bringing Structure to Naturalness: On the Naturalness of ASTs. CoRR Profir-Petru Pârtachi, Mahito Sugiyama
2025	J	`jnl`	Large language models: assessment for singularity. AI Soc. Ryunosuke Ishizaki, Mahito Sugiyama
2025	A*	`conf`	Linear Mode Connectivity in Differentiable Tree Ensembles. ICLR Ryuichi Kanoh, Mahito Sugiyama
2025	J	`jnl`	New Evidence of the Two-Phase Learning Dynamics of Neural Networks. CoRR Zhanpeng Zhou, Yongyi Yang, Mahito Sugiyama, Junchi Yan
2025	J	`jnl`	On the Cone Effect in the Learning Dynamics. CoRR Zhanpeng Zhou, Yongyi Yang, Jie Ren, Mahito Sugiyama, Junchi Yan
2025	A	`conf`	Optimal Submanifold Structure in Log-linear Models. UAI Zhou Derun, Mahito Sugiyama
2024	J	`jnl`	A Complete Decomposition of KL Error using Refined Information and Mode Interaction Selection. CoRR James Enouen, Mahito Sugiyama
2024	—	`conf`	Bringing Structure to Naturalness: On the Naturalness of ASTs. ICSE Companion Profir-Petru Pârtachi, Mahito Sugiyama
2024	J	`jnl`	How graph features from message passing affect graph classification and regression? Intell. Data Anal. Masatsugu Yamada, Mahito Sugiyama
2024	J	`jnl`	Linear Mode Connectivity in Differentiable Tree Ensembles. CoRR Ryuichi Kanoh, Mahito Sugiyama
2024	A*	`conf`	Neural Tangent Kernels for Axis-Aligned Tree Ensembles. ICML Ryuichi Kanoh, Mahito Sugiyama
2024	J	`jnl`	Pseudo-Non-Linear Data Augmentation via Energy Minimization. CoRR Pingbang Hu, Mahito Sugiyama
2024	J	`jnl`	StiefelGen: A Simple, Model Agnostic Approach for Time Series Data Augmentation over Riemannian Manifolds. CoRR Prasad Cheema, Mahito Sugiyama
2023	A*	`conf`	Analyzing Tree Architectures in Ensembles via Neural Tangent Kernel. ICLR Ryuichi Kanoh, Mahito Sugiyama
2023	A*	`conf`	Many-body Approximation for Non-negative Tensors. NeurIPS Kazu Ghalamkari, Mahito Sugiyama, Yoshinobu Kawahara
2023	J	`jnl`	Molecular Graph Generation by Decomposition and Reassembling. CoRR Masatsugu Yamada, Mahito Sugiyama
2023	J	`jnl`	Unsupervised Tensor Based Feature Extraction From Multivariate Time Series. IEEE Access Kiyotaka Matsue, Mahito Sugiyama
2022	J	`jnl`	A Neural Tangent Kernel Formula for Ensembles of Soft Trees with Arbitrary Architectures. CoRR Ryuichi Kanoh, Mahito Sugiyama
2022	A*	`conf`	A Neural Tangent Kernel Perspective of Infinite Tree Ensembles. ICLR Ryuichi Kanoh, Mahito Sugiyama
2022	A	`conf`	Fast Rank-1 NMF for Missing Data with KL Divergence. AISTATS Kazu Ghalamkari, Mahito Sugiyama
2022	J	`jnl`	Many-Body Approximation for Tensors. CoRR Kazu Ghalamkari, Mahito Sugiyama
2022	J	`jnl`	Unsupervised feature extraction from multivariate time series for outlier detection. Intell. Data Anal. Kiyotaka Matsue, Mahito Sugiyama
2021	J	`jnl`	A Closed Form Solution to Best Rank-1 Tensor Approximation via KL divergence Minimization. CoRR Kazu Ghalamkari, Mahito Sugiyama
2021	J	`jnl`	A Neural Tangent Kernel Perspective of Infinite Tree Ensembles. CoRR Ryuichi Kanoh, Mahito Sugiyama
2021	J	`jnl`	Fast Rank-1 NMF for Missing Data with KL Divergence. CoRR Kazu Ghalamkari, Mahito Sugiyama
2021	A*	`conf`	Fast Tucker Rank Reduction for Non-Negative Tensors Using Mean-Field Approximation. NeurIPS Kazu Ghalamkari, Mahito Sugiyama
2021	A	`conf`	Hierarchical probabilistic model for blind source separation via Legendre transformation. UAI Simon Luo, Lamiae Azizi, Mahito Sugiyama
2021	A	`conf`	Investigating Overparameterization for Non-Negative Matrix Factorization in Collaborative Filtering. RecSys Yuhi Kawakami, Mahito Sugiyama
2021	J	`jnl`	Unintended Effects on Adaptive Learning Rate for Training Neural Network with Output Scale Change. CoRR Ryuichi Kanoh, Mahito Sugiyama
2021	B	`conf`	Unsupervised Tensor based Feature Extraction and Outlier Detection for Multivariate Time Series. DSAA Kiyotaka Matsue, Mahito Sugiyama
2020	J	`jnl`	A Geometric Look at Double Descent Risk: Volumes, Singularities, and Distinguishabilities. CoRR Prasad Cheema, Mahito Sugiyama
2020	J	`jnl`	Additive Poisson Process: Learning Intensity of Higher-Order Interaction in Stochastic Processes. CoRR Simon Luo, Feng Zhou, Lamiae Azizi, Mahito Sugiyama
2020	B	`conf`	Coordinate Descent Method for Log-linear Model on Posets. DSAA Shota Hayashi, Mahito Sugiyama, Shin Matsushima
2020	J	`jnl`	Rank Reduction, Matrix Balancing, and Mean-Field Approximation on Statistical Manifold. CoRR Kazu Ghalamkari, Mahito Sugiyama
2020	—	`conf`	Testing machine learning code using polyhedral region. ESEC/SIGSOFT FSE Md Sohel Ahmed, Fuyuki Ishikawa, Mahito Sugiyama
2019	A*	`conf`	Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions. AAAI Simon Luo, Mahito Sugiyama
2019	J	`jnl`	Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions. CoRR Simon Luo, Mahito Sugiyama
2019	A*	`conf`	Finding Statistically Significant Interactions between Continuous Features. IJCAI Mahito Sugiyama, Karsten M. Borgwardt
2019	J	`jnl`	Hierarchical Probabilistic Model for Blind Source Separation via Legendre Transformation. CoRR Simon Luo, Lamiae Azizi, Mahito Sugiyama
2019	J	`jnl`	Summarizing significant subgraphs by probabilistic logic programming. Intell. Data Anal. Elena Bellodi, Ken Satoh, Mahito Sugiyama
2018	J	`jnl`	Learning Graph Representation via Formal Concept Analysis. CoRR Yuka Yoneda, Mahito Sugiyama, Takashi Washio
2018	A*	`conf`	Legendre Decomposition for Tensors. NeurIPS Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda
2018	J	`jnl`	Legendre Tensor Decomposition. CoRR Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda
2018	J	`jnl`	Transductive Boltzmann Machines. CoRR Mahito Sugiyama, Koji Tsuda, Hiroyuki Nakahara
2018	J	`jnl`	graphkernels: R and Python packages for graph comparison. Bioinform. Mahito Sugiyama, M. Elisabetta Ghisu, Felipe Llinares-López, Karsten M. Borgwardt
2017	J	`jnl`	Significant Pattern Mining on Continuous Variables. CoRR Mahito Sugiyama, Karsten M. Borgwardt
2017	A*	`conf`	Tensor Balancing on Statistical Manifold. ICML Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda
2017	J	`jnl`	Tensor Balancing on Statistical Manifold. CoRR Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda
2016	J	`jnl`	Information Decomposition on Structured Space. CoRR Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda
2016	B	`conf`	Information decomposition on structured space. ISIT Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda
2015	A*	`conf`	Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing. KDD Felipe Llinares-López, Mahito Sugiyama, Laetitia Papaxanthos, Karsten M. Borgwardt
2015	J	`jnl`	Genome-wide detection of intervals of genetic heterogeneity associated with complex traits. Bioinform. Felipe Llinares-López, Dominik G. Grimm, Dean A. Bodenham, Udo Gieraths, Mahito Sugiyama, Beth Rowan, Karsten M. Borgwardt
2015	—	`conf`	Halting in Random Walk Kernels. NIPS Mahito Sugiyama, Karsten M. Borgwardt
2015	A	`conf`	Significant Subgraph Mining with Multiple Testing Correction. SDM Mahito Sugiyama, Felipe Llinares-López, Niklas Kasenburg, Karsten M. Borgwardt
2014	—	`conf`	Detecting Anomalous Subgraphs on Attributed Graphs via Parametric Flow. JSAI-isAI Workshops Mahito Sugiyama, Keisuke Otaki
2014	J	`jnl`	Identifying Higher-order Combinations of Binary Features. CoRR Felipe Llinares, Mahito Sugiyama, Karsten M. Borgwardt
2014	A	`conf`	Multi-Task Feature Selection on Multiple Networks via Maximum Flows. SDM Mahito Sugiyama, Chloé-Agathe Azencott, Dominik G. Grimm, Yoshinobu Kawahara, Karsten M. Borgwardt
2014	J	`jnl`	Significant Subgraph Mining with Multiple Testing Correction. CoRR Mahito Sugiyama, Felipe Llinares-López, Niklas Kasenburg, Karsten M. Borgwardt
2013	J	`jnl`	Efficient network-guided multi-locus association mapping with graph cuts. Bioinform. Chloé-Agathe Azencott, Dominik G. Grimm, Mahito Sugiyama, Yoshinobu Kawahara, Karsten M. Borgwardt
2013	J	`jnl`	Learning figures with the Hausdorff metric by fractals - towards computable binary classification. Mach. Learn. Mahito Sugiyama, Eiju Hirowatari, Hideki Tsuiki, Akihiro Yamamoto
2013	A*	`conf`	Measuring Statistical Dependence via the Mutual Information Dimension. IJCAI Mahito Sugiyama, Karsten M. Borgwardt
2013	—	`conf`	Outliers on Concept Lattices. JSAI-isAI Workshops Mahito Sugiyama
2013	—	`conf`	Rapid Distance-Based Outlier Detection via Sampling. NIPS Mahito Sugiyama, Karsten M. Borgwardt
2013	J	`jnl`	Semi-supervised learning on closed set lattices. Intell. Data Anal. Mahito Sugiyama, Akihiro Yamamoto
2012	J	`jnl`	Privacy Preserving Using Dummy Data for Set Operations in Itemset Mining Implemented with ZDDs. IEICE Trans. Inf. Syst. Keisuke Otaki, Mahito Sugiyama, Akihiro Yamamoto
2012	J	`jnl`	Semi-Supervised Ligand Finding Using Formal Concept Analysis. Inf. Media Technol. Mahito Sugiyama, Kentaro Imajo, Keisuke Otaki, Akihiro Yamamoto
2011	A*	`conf`	A Fast and Flexible Clustering Algorithm Using Binary Discretization. ICDM Mahito Sugiyama, Akihiro Yamamoto
2011	—	`conf`	Discovering Ligands for TRP Ion Channels Using Formal Concept Analysis. ILP (Late Breaking Papers) Mahito Sugiyama, Kentaro Imajo, Keisuke Otaki, Akihiro Yamamoto
2011	Misc	`conf`	Semi-supervised Learning for Mixed-Type Data via Formal Concept Analysis. ICCS Mahito Sugiyama, Akihiro Yamamoto
2011	—	`conf`	The Minimum Code Length for Clustering Using the Gray Code. ECML/PKDD (3) Mahito Sugiyama, Akihiro Yamamoto
2010	B	`conf`	Learning Figures with the Hausdorff Metric by Fractals. ALT Mahito Sugiyama, Eiju Hirowatari, Hideki Tsuiki, Akihiro Yamamoto
2010	C	`conf`	The Coding Divergence for Measuring the Complexity of Separating Two Sets. ACML Mahito Sugiyama, Akihiro Yamamoto