Searching for bacterial pathogens in the Digital Ocean—Executive Summary
@article{Sugiyama2017CIESM1,
Author = {Giuliano, L. and Dorman, C. and Bowler, C. and Sugiyama, M. and Vezzulli, L. and Czerucka, D. and Le Roux, F. and D'Auria, G. and Troussellier, M. and Briand, F.},
Title = {Searching for bacterial pathogens in the Digital Ocean---Executive Summary},
Journal = {CIESM Workshop Monograph},
Volume = {49},
Pages = {5--25},
Year = {2017}}
Finding Statistically Significant Patterns from Data
@article{Sugiyama2017CIESM2,
Author = {Sugiyama, M.},
Title = {Finding Statistically Significant Patterns from Data},
Journal = {CIESM Workshop Monograph},
Volume = {49},
Pages = {53--58},
Year = {2017}}
Pattern Mining with Statistical Significance (in Japanese)
@article{Sugiyama2017OS,
Author = {Sugiyama, M.},
Title = {Pattern Mining with Statistical Significance (in Japanese)},
Journal = {Communications of the Operations Research Society of Japan},
Volume = {62},
Number = {4},
Pages = {226--232},
Year = {2017}}
graphkernels: R and Python Packages for Graph Comparison
@article{Sugiyama2018Bioinfo,
Author = {Sugiyama, M. and Ghisu, E. and Llinares-L{\'o}pez, F. and Borgwardt, K. M.},
Title = {graphkernels: R and Python Packages for Graph Comparison},
Journal = {Bioinformatics},
Volume = {34},
Number = {3},
Pages = {530--532},
Year = {2018}}
Genome-Wide Detection of Intervals of Genetic Heterogeneity Associated with Complex Traits
@article{Llinares2015ISMB,
Author = {Llinares-L{\'o}pez, F. and Grimm, D. G. and Bodenham, D. A. and Gieraths, U. and Sugiyama, M. and Rowan, B. and Borgwardt, K. M.},
Title = {Genome-Wide Detection of Intervals of Genetic Heterogeneity Associated with Complex Traits},
Journal = {Bioinformatics},
Volume = {31},
Number = {12},
Pages = {i240--i249},
Year = {2015}}
Efficient Network-Guided Multi-Locus Association Mapping with Graph Cut
@article{Azencott2013ISMB,
Author = {Azencott, C.-A. and Grimm, D. G. and Sugiyama, M. and Kawahara, Y. and Borgwardt, K. M.},
Title = {Efficient Network-Guided Multi-Locus Association Mapping with Graph Cut},
Journal = {Bioinformatics},
Volume = {29},
Number = {13},
Pages = {i171--i179},
Year = {2013}}
Semi-Supervised Learning on Closed Set Lattices
@article{SugiyamaIDA01,
Author = {Sugiyama, M. and Yamamoto, A.},
Title = {Semi-Supervised Learning on Closed Set Lattices},
Journal = {Intelligent Data Analysis},
Volume = {17},
Number = {3},
Pages = {399--421},
Publisher = {IOS Press},
Year = {2013}}
Learning Figures with the Hausdorff Metric by Fractals—Towards Computable Binary Classification
@article{SugiyamaMLJ01,
Author = {Sugiyama, M. and Hirowatari, E. and Tsuiki, H. and Yamamoto, A.},
Title = {Learning Figures with the Hausdorff Metric by Fractals---Towards Computable Binary Classification},
Journal = {Machine Learning},
Volume = {90},
Number = {1},
Pages = {91--126},
Publisher = {Springer},
Year = {2013}}
Privacy Preserving Using Dummy Data for Set Operations in Itemset Mining Implemented with ZDDs
@article{OtakiIEICE01,
Author = {Otaki, K. and Sugiyama, M. and Yamamoto, A.},
Title = {Privacy Preserving Using Dummy Data for Set Operations in Itemset Mining Implemented with {ZDD}s},
Journal = {IEICE Transactions on Information and Systems},
Volume = {E95-D},
Number = {12},
Pages = {3017--3025},
Publisher = {IEICE},
Year = {2012}}
Semi-Supervised Ligand Finding Using Formal Concept Analysis
@article{SugiyamaTOM01,
Author = {Sugiyama, M. and Imajo, K. and Otaki, K. and Yamamoto, A.},
Title = {Semi-Supervised Ligand Finding Using Formal Concept Analysis},
Journal = {IPSJ Transactions on Mathematical Modeling and Its Applications (TOM)},
Volume = {5},
Number = {2},
Pages = {39--48},
Publisher = {The Information Processing Society of Japan (IPSJ)},
Year = {2012}}
Finding Statistically Significant Interactions between Continuous Features
@inproceedings{Sugiyama2019Finding,
Author = {Sugiyama, M. and Borgwardt, K},
Title = {Finding Statistically Significant Interactions between Continuous Features},
Booktitle = {Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019)},
Pages = {3490--3498},
Address = {Macao, China},
Month = {August},
Year = {2019}}
Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions
@inproceedings{Luo2019AAAI,
Author = {Luo, S., Sugiyama, M.},
Title = {Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions},
Booktitle = {Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI-19)},
Volume = {33},
Number = {01},
Pages = {4488--4495},
Address = {Hawaii, USA},
Month = {January--February},
Year = {2019}}
Legendre Decomposition for Tensors
@inproceedings{Sugiyama2018NeurIPS,
Author = {Sugiyama, M. and Nakahara, H. and Tsuda, K.},
Title = {Legendre Decomposition for Tensors},
Booktitle = {Advances in Neural Information Processing Systems 31},
Pages = {8825--8835},
Address = {Montréal, Canada},
Month = {December},
Year = {2018}}
Tensor Balancing on Statistical Manifold
@inproceedings{Sugiyama2017ICML,
Author = {Sugiyama, M. and Nakahara, H. and Tsuda, K.},
Title = {Tensor Balancing on Statistical Manifold},
Booktitle = {Proceedings of the 34th International Conference on Machine Learning (ICML)},
Volume = {70},
Pages = {3270--3279},
Series = {Proceedings of Machine Learning Research},
Address = {Sydney, Australia},
Month = {August},
Year = {2017}}
Information Decomposition on Structured Space
@inproceedings{Sugiyama2016ISIT,
Author = {Sugiyama, M. and Nakahara, H. and Tsuda, K.},
Title = {Information Decomposition on Structured Space},
Booktitle = {2016 IEEE International Symposium on Information Theory (ISIT)},
Pages = {575--579},
Address = {Barcelona, Spain},
Month = {July},
Year = {2016}}
Halting in Random Walk Kernels
@inproceedings{Sugiyama2015NIPS,
Author = {Sugiyama, M. and Borgwardt, K. M.},
Title = {Halting in Random Walk Kernels},
Booktitle = {Advances in Neural Information Processing Systems 28},
Pages = {1630--1638},
Address = {Montréal, Canada},
Month = {December},
Year = {2015}}
Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing
@inproceedings{Llinares2015KDD,
Author = {Llinares-L{\'o}pez, F. and Sugiyama, M. and Papaxanthos, L. and Borgwardt, K. M.},
Title = {Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing},
Booktitle = {Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
Pages = {725--734},
Address = {Sydney, Australia},
Month = {August},
Year = {2015}}
Significant Subgraph Mining with Multiple Testing Correction
@inproceedings{Sugiyama2015SDM,
Author = {Sugiyama, M. and Llinares-L{\'o}pez, F. and Kasenburg, N. and Borgwardt, K. M.},
Title = {Significant Subgraph Mining with Multiple Testing Correction},
Booktitle = {Proceedings of the 2015 SIAM International Conference on Data Mining},
Pages = {37--45},
Address = {Vancouver, British Columbia, Canada},
Month = {April--May},
Year = {2015}}
Multi-Task Feature Selection on Multiple Networks via Maximum Flows
@inproceedings{Sugiyama2014SDM,
Author = {Sugiyama, M. and Azencott, C.-A. and Grimm, D. G. and Kawahara, Y. and Borgwardt, K. M.},
Title = {Multi-Task Feature Selection on Multiple Networks via Maximum Flows},
Booktitle = {Proceedings of the 2014 SIAM International Conference on Data Mining},
Pages = {199--207},
Address = {Philadelphia, Pennsylvania, USA},
Month = {April},
Year = {2014}}
Rapid Distance-Based Outlier Detection via Sampling
@inproceedings{Sugiyama2013NIPS,
Author = {Sugiyama, M. and Borgwardt, K. M.},
Title = {Rapid Distance-Based Outlier Detection via Sampling},
Booktitle = {Advances in Neural Information Processing Systems 26},
Pages = {467--475},
Address = {Lake Tahoe, Nevada, USA},
Month = {December},
Year = {2013}}
Measuring Statistical Dependence via the Mutual Information Dimension
@inproceedings{Sugiyama2013IJCAI,
Author = {Sugiyama, M. and Borgwardt, K. M.},
Title = {Measuring Statistical Dependence via the Mutual Information Dimension},
Booktitle = {Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013)},
Pages = {1692--1698},
Address = {Beijing, China},
Month = {August},
Year = {2013}}
A Fast and Flexible Clustering Algorithm Using Binary Discretization
@inproceedings{Sugiyama2011ICDM,
Author = {Sugiyama, M. and Yamamoto, A.},
Title = {A Fast and Flexible Clustering Algorithm Using Binary Discretization},
Booktitle = {Proceedings of the 2011 IEEE International Conference on Data Mining (ICDM 2011)},
Pages = {1212--1217},
Address = {Vancouver, Canada},
Month = {December},
Year = {2011}}
The Minimum Code Length for Clustering Using the Gray Code
@inproceedings{Sugiyama2011ECML,
Author = {Sugiyama, M. and Yamamoto, A.},
Title = {The Minimum Code Length for Clustering Using the {G}ray Code},
Editor = {Gunopulos, D. and Hofmann, T. and Malerba, D. and Vazirgiannis, M.},
Booktitle = {Machine Learning and Knowledge Discovery in Databases},
Series = {Lecture Notes in Computer Science},
Volume = {6913},
Pages = {365--380},
Publisher = {Springer},
Year = {2011}}
Semi-Supervised Learning for Mixed-Type Data via Formal Concept Analysis
@inproceedings{Sugiyama2011ICCS,
Author = {Sugiyama, M. and Yamamoto, A.},
Title = {Semi-Supervised Learning for Mixed-Type Data via Formal Concept Analysis},
Editor = {Andrews, S. and Polovina, S. and Hill, R. and Akhgar, B.},
Booktitle = {Conceptual Structures for Discovering Knowledge},
Series = {Lecture Notes in Computer Science},
Volume = {6828},
Pages = {284--297},
Publisher = {Springer},
Year = {2011}}
The Coding Divergence for Measuring the Complexity of Separating Two Sets
@inproceedings{Sugiyama2010ACML,
Author = {Sugiyama, M. and Yamamoto, A.},
Title = {The Coding Divergence for Measuring the Complexity of Separating Two Sets},
Editor = {Sugiyama, M. and Yang, Q.},
Booktitle = {Proceedings of 2nd Asian Conference on Machine Learning (ACML2010)},
Series = {JMLR Workshop and Conference Proceedings},
Volume = {13},
Pages = {127--143},
Address = {Tokyo, Japan},
Month = {November},
Year = {2010}}
Learning Figures with the Hausdorff Metric by Fractals
@inproceedings{Sugiyama2010ALT,
Author = {Sugiyama, M. and Hirowatari, E. and Tsuiki, H. and Yamamoto, A.},
Title = {Learning Figures with the {H}ausdorff Metric by Fractals},
Editor = {Hutter, M. and Stephan, F. and Vovk, V. and Zeugmann, T.},
Booktitle = {Algorithmic Learning Theory},
Series = {Lecture Notes in Computer Science},
Volume = {6331},
Pages = {315--329},
Publisher = {Springer},
Year = {2010}}
Learning Graph Representation via Formal Concept Analysis
@inproceedings{Yoneda2018R2L,
Author = {Yoneda, Y. and Sugiyama, M. and Washio, T.},
Title = {Learning Graph Representation via Formal Concept Analysis},
Booktitle = {Proceedings of Relational Representation Learning},
Address = {Montréal, Canada},
Month = {December},
Year = {2018}}
Finding Combinations of Binary Variables with Guaranteed Accuracy
@inproceedings{Baba2016ADAPTIVE,
Author = {Baba, Y. and Sugiyama, M. and Washio, T.},
Title = {Finding Combinations of Binary Variables with Guaranteed Accuracy},
Booktitle = {Proceedings of Adaptive and Scalable Nonparametric Methods in Machine Learning},
Address = {Barcelona, Spain},
Month = {December},
Year = {2016}}
Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing
@inproceedings{Llinares2015BIOKDD,
Author = {Llinares-L{\'o}pez, F. and Sugiyama, M. and Papaxanthos, L. and Borgwardt, K. M.},
Title = {Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing},
Booktitle = {Proceedings of 14th International Workshop on Data Mining in Bioinformatics (BIOKDD'15)},
Address = {Sydney, Australia},
Month = {August},
Year = {2015}}
Detecting Anomalous Subgraphs on Attributed Graphs via Parametric Flow
@inproceedings{Sugiyama2014GABA,
Author = {Sugiyama, M. and Otaki, K.},
Title = {Detecting Anomalous Subgraphs on Attributed Graphs via Parametric Flow},
Editor = {Murata, T. and Mineshima, K. and Bekki, D.},
Booktitle = {New Frontiers in Artificial Intelligence},
Series = {Lecture Notes in Computer Science},
Volume = {9067},
Pages = {340--355},
Publisher = {Springer},
Address = {Yokohama, Japan},
Year = {2015}}
Rapid Distance-Based Outlier Detection via Sampling
@inproceedings{Sugiyama2013RMML,
Author = {Sugiyama, M. and Borgwardt, K. M.},
Title = {Rapid Distance-Based Outlier Detection via Sampling},
Booktitle = {NIPS 2013 Randomized Methods for Machine Learning Workshop (RMML 2013)},
Address = {Lake Tahoe, Nevada, USA},
Month = {December},
Year = {2013}}
Outliers on Concept Lattices
@inproceedings{Sugiyama2013DDS,
Author = {Sugiyama, M.},
Title = {Outliers on Concept Lattices},
Editor = {Nakano, Y. and Satoh, K. and Bekki, D.},
Booktitle = {New Frontiers in Artificial Intelligence},
Series = {Lecture Notes in Computer Science},
Volume = {8417},
Pages = {352--368},
Publisher = {Springer},
Address = {Yokohama, Japan},
Year = {2014}}
High-throughput Data Stream Classification on Trees
@inproceedings{Sugiyama2011ALSIP,
Author = {Sugiyama, M. and Yoshioka, T. and Yamamoto, A.},
Title = {High-throughput Data Stream Classification on Trees},
Booktitle = {Proceedings of Second Workshop on Algorithms for Large-Scale Information Processing in Knowledge Discovery (ALSIP 2011)},
Address = {Kagawa, Japan},
Month = {December},
Year = {2011}}
Fast Clustering Based on the Gray-Code
@inproceedings{Sugiyama2011LLLL,
Author = {Sugiyama, M. and Yamamoto, A.},
Title = {Fast Clustering Based on the {G}ray-Code},
Booktitle = {Proceedings of 7th Workshop on Learning with Logics and Logics for Learning (LLLL2011)},
Pages = {42},
Address = {Osaka, Japan},
Month = {March},
Year = {2011}}
Learning Figures with the Hausdorff Metric by Self-similar Sets
@inproceedings{Sugiyama2009LLLL,
Author = {Sugiyama, M. and Hirowatari, E. and Tsuiki, H. and Yamamoto, A.},
Title = {Learning Figures with the {H}ausdorff Metric by Self-similar Sets},
Booktitle = {Proceedings of 6th Workshop on Learning with Logics and Logics for Learning (LLLL2009)},
Pages = {27--34},
Address = {Kyoto, Japan},
Month = {July},
Year = {2009}}
Learning from Real-Valued Data with the Model Inference Mechanism through the Gray-Code Embedding
@inproceedings{Sugiyama2006LLLL,
Author = {Sugiyama, M. and Hirowatari, E. and Tsuiki, H. and Yamamoto, A.},
Title = {Learning from Real-Valued Data with the Model Inference Mechanism through the {G}ray-Code Embedding},
Booktitle = {Proceedings of 4th Workshop on Learning with Logics and Logics for Learning (LLLL2006)},
Pages = {31--37},
Address = {Tokyo, Japan},
Month = {June},
Year = {2006}}