研究業績

プレプリント

  1. Sugiyama, M., Borgwardt, K.M.:
    Significant Pattern Mining on Continuous Variables,
    arXiv:1702.08694.

著書

  1. 小林 茂夫, 杉山 麿人:
    生命科学研究に成功するための統計法ノート,
    講談社, 2009年4月.

総説

  1. 杉山 麿人:
    統計的有意性を担保するパターンマイニング技術,
    オペレーションズ・リサーチ誌, 62(4), 2017年4月.

学術雑誌

  1. Sugiyama, M., Ghisu, E., Llinares-López, F., Borgwardt, K.M.:
    graphkernels: R and Python Packages for Graph Comparison,
    Bioinformatics, 2017 (in press)
  2. Llinares-López, F., Grimm, D.G., Bodenham, D.A., Gieraths, U., Sugiyama, M., Rowan, B., Borgwardt, K.M.:
    Genome-Wide Detection of Intervals of Genetic Heterogeneity Associated with Complex Traits,
    Bioinformatics, 31(12), i240—i249, 2015 (Proceedings of ISMB/ECCB 2015).
  3. Azencott, C.-A., Grimm, D.G., Sugiyama, M., Kawahara, Y., Borgwardt, K.M.:
    Efficient Network-Guided Multi-Locus Association Mapping with Graph Cut,
    Bioinformatics, 29(13), i171—i179, 2013 (Proceedings of ISMB/ECCB 2013).
  4. Sugiyama, M., Yamamoto, A.:
    Semi-Supervised Learning on Closed Set Lattices,
    Intelligent Data Analysis, 17(3), 399—421, 2013.
  5. Sugiyama, M., Hirowatari, E., Tsuiki, H., Yamamoto, A.:
    Learning Figures with the Hausdorff Metric by Fractals—Towards Computable Binary Classification,
    Machine Learning, 90(1), 91—126, 2013.
  6. Otaki, K., Sugiyama, M., Yamamoto, A.:
    Privacy Preserving Using Dummy Data for Set Operations in Itemset Mining Implemented with ZDDs,
    IEICE Trans. Inf. & Syst., E95-D(12), 3017—3025, 2012.
  7. Sugiyama, M., Imajo, K., Otaki, K., Yamamoto, A.:
    Semi-Supervised Ligand Finding Using Formal Concept Analysis,
    IPSJ TOM, 5(2), 39—48, 2012.

国際会議(査読付)

  1. Sugiyama, M., Nakahara, H., Tsuda, K.:
    Tensor Balancing on Statistical Manifold,
    ICML 2017.
  2. Sugiyama, M., Nakahara, H., Tsuda, K.:
    Information Decomposition on Structured Space,
    IEEE ISIT 2016.
  3. Sugiyama, M., Borgwardt, K.M.:
    Halting in Random Walk Kernels,
    NIPS 2015.
  4. Llinares-López, F., Sugiyama, M., Papaxanthos, L., Borgwardt, K.M.:
    Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing,
    ACM KDD 2015.
  5. Llinares-López, F., Grimm, D.G., Bodenham, D.A., Gieraths, U., Sugiyama, M., Rowan, B., Borgwardt, K.M.:
    Genome-Wide Detection of Intervals of Genetic Heterogeneity Associated with Complex Traits,
    ISMB/ECCB 2015. (Proceedings appear in Bioinformatics)
  6. Sugiyama, M., Llinares-López, F., Kasenburg, N., Borgwardt, K.M.:
    Significant Subgraph Mining with Multiple Testing Correction,
    SIAM SDM 2015.
  7. Sugiyama, M., Azencott, C.-A., Grimm, D.G., Kawahara, Y., Borgwardt, K.M.:
    Multi-Task Feature Selection on Multiple Networks via Maximum Flows,
    SIAM SDM 2014.
  8. Sugiyama, M., Borgwardt, K.M.:
    Rapid Distance-Based Outlier Detection via Sampling,
    NIPS 2013.
  9. Azencott, C.-A., Grimm, D.G., Sugiyama, M., Kawahara, Y., Borgwardt, K.M.:
    Efficient Network-Guided Multi-Locus Association Mapping with Graph Cut,
    ISMB/ECCB 2013. (Proceedings appear in Bioinformatics)
  10. Sugiyama, M., Borgwardt, K.M.:
    Measuring Statistical Dependence via the Mutual Information Dimension,
    IJCAI 2013.
  11. Sugiyama, M., Yamamoto, A.:
    A Fast and Flexible Clustering Algorithm Using Binary Discretization,
    IEEE ICDM 2011.
  12. Sugiyama, M., Yamamoto, A.:
    The Minimum Code Length for Clustering Using the Gray Code,
    ECML PKDD 2011 (LNCS 6913).
  13. Sugiyama, M., Yamamoto, A.:
    Semi-Supervised Learning for Mixed-Type Data via Formal Concept Analysis,
    ICCS 2011 (LNCS 6828).

    (There is an extended journal version)

  14. Sugiyama, M., Yamamoto, A.:
    The Coding Divergence for Measuring the Complexity of Separating Two Sets,
    ACML 2010 (JMLR Workshop and Conference Proceedings 13).
  15. Sugiyama, M., Hirowatari, E., Tsuiki, H., Yamamoto, A.:
    Learning Figures with the Hausdorff Metric by Fractals,
    ALT 2010 (LNCS 6331).

    (There is an extended journal version)

国際ワークショップ(査読付)

  1. Baba, Y., Sugiyama, M., Washio, T.:
    Finding Combinations of Binary Variables with Guaranteed Accuracy,
    NIPS 2016 ADAPTIVE.
  2. Llinares-López, F., Sugiyama, M., Papaxanthos, L., Borgwardt, K.M.:
    Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing,
    BIOKDD'15.
  3. Sugiyama, M., Otaki, K.:
    Detecting Anomalous Subgraphs on Attributed Graphs via Parametric Flow,
    GABA 2014 (LNCS 9067).
  4. Sugiyama, M., Borgwardt, K.M.:
    Rapid Distance-Based Outlier Detection via Sampling,
    RMML 2013.
  5. Sugiyama, M.:
    Outliers on Concept Lattices,
    DDS13 (LNCS 8417).
  6. Sugiyama, M., Yoshioka, T., Yamamoto, A.:
    High-throughput Data Stream Classification on Trees,
    ALSIP 2011.
  7. Sugiyama, M., Yamamoto, A.:
    Fast Clustering Based on the Gray-Code,
    LLLL 2011.
  8. Sugiyama, M., Hirowatari, E., Tsuiki, H., Yamamoto, A.:
    Learning Figures with the Hausdorff Metric by Self-similar Sets,
    LLLL 2009.
  9. Sugiyama, M., Hirowatari, E., Tsuiki, H., Yamamoto, A.:
    Learning from Real-Valued Data with the Model Inference Mechanism through the Gray-Code Embedding,
    LLLL 2006.

国際会議・ワークショップ

  1. Sugiyama, M.:
    Significant Pattern Mining on Graphs,
    MCP 2017.
  2. Sugiyama, M., Imajo, K., Otaki, K., Yamamoto, A.:
    Discovering Ligands for TRP Ion Channels Using Formal Concept Analysis,
    ILP 2011. (There is an extended journal version)
  3. Kawai, Y., Sugiyama, M., Yamamoto, A.:
    Mining RNA Families with Structure Histograms,
    DMSS 2011.

学会・研究会

  1. 米田 友花, 杉山 麿人, 鷲尾 隆:
    離散化による解釈可能な分類モデルの構築,
    第31回人工知能学会全国大会, 2K2-4, 2017年5月.
  2. 杉山 麿人, 中原 裕之, 津田 宏治:
    順序構造上の情報幾何的な統計解析,
    第103回人工知能基本問題研究会資料, SIG-FPAI-B506-10, pp. 51-56, 2017年3月.
  3. 馬場 祥人, 杉山 麿人, 鷲尾 隆:
    サンプリングを用いた精度保証つき頻出パターンマイニング,
    第30回人工知能学会全国大会, 3I4-2, 2016年6月.
  4. 杉山 麿人, Borgwardt, K.M.:
    ランダムウォークグラフカーネルの停止に関する解析,
    第18回情報論的学習理論ワークショップ (IBIS2015), 2015年11月.
  5. 馬場 祥人, 杉山 麿人, 鷲尾 隆:
    サンプリングを用いた高速頻出パターンマイニング,
    第29回人工知能学会全国大会, 3C4-2, 2015年6月.
  6. 杉山 麿人, Llinares-López, F., Kasenburg, N., Borgwardt, K.M.:
    グラフマイニングでの多重検定補正,
    情報処理学会第77回全国大会, 2015年3月.
  7. Sugiyama, M., Imajo, K., Otaki, K., Yamamoto, A.:
    Semi-Supervised Ligand Finding Using Formal Concept Analysis,
    第86回MPS・第27回BIO合同研究発表会, IPSJ SIG Technical Report, vol.2011-MPS-86, no.28, 2011年12月.
  8. 杉山 麿人, 山本 章博:
    2進符号化を活用した高速かつ柔軟なクラスタリング,
    第25回人工知能学会全国大会, 1P2-lb-3in, 2011年6月.
  9. 秦 亮一, 池田 真土里, 杉山 麿人, 山本 章博:
    質問学習とメタアルゴリズムの組合せによる文字列画像検索,
    信学技報, vol. 110, no. 476, IBISML2010-120, pp. 115-122, 2011年3月.
  10. 吉岡 正志, 杉山 麿人, 山本 章博:
    符号化ダイバージェンスを用いたクラス分類のためのオンラインアルゴリズム,
    信学技報, vol. 110, no. 476, IBISML2010-117, pp. 93-100, 2011年3月.
  11. 福村 貴志, 杉山 麿人, 山本 章博:
    木構造を利用した自然画像の部分領域検索とフラクタル圧縮・マイニングへの応用,
    信学技報, vol. 110, no. 476, IBISML2010-112, pp. 55-62, 2011年3月.
  12. 杉山 麿人, 山本 章博:
    離散量と連続量が混在するデータに対する形式概念分析を用いた半教師あり学習,
    第80回人工知能基本問題研究会資料, SIG-FPAI-B003, pp. 7-14, 2010年11月.
  13. 杉山 麿人, 山本 章博:
    グレイ符号化ダイバージェンスによる連続データからの計算論的知識発見,
    第78回人工知能基本問題研究会資料, SIG-FPAI-B001-03, pp. 17-24, 2010年7月.
  14. 杉山 麿人, 山本 章博:
    符号化ダイバージェンスによる2つの集合の異なり具合の定量化,
    信学技報, vol. 110, no. 76, IBISML2010-26, pp. 181-187, 2010年6月.
  15. 杉山 麿人, 山本 章博:
    計算論的学習理論に基づく統計的仮説検定の代替手法,
    第77回人工知能基本問題研究会資料, SIG-FPAI-A904, pp. 43-48, 2010年3月.
    (2009年度 人工知能学会 研究会優秀賞)
  16. 杉山 麿人, 廣渡 栄寿, 立木 秀樹, 山本 章博:
    ハウスドルフ距離を用いたフラクタルによる図形の学習,
    第74回人工知能基本問題研究会資料, SIG-FPAI-A901, pp. 31-38, 2009年9月.
  17. 杉山 麿人, 廣渡 栄寿, 立木 秀樹, 山本 章博:
    グレイコードとモデル推論を利用した実数値関数の学習,
    第62回人工知能基本問題研究会資料, SIG-FPAI-A504, pp. 47-54, 2006年3月.

口頭発表

  1. 杉山 麿人:
    Learning Figures with the Hausdorff Metric by Self-similar Sets,
    SLACS 2009, 2009年8月.
  2. 杉山 麿人, 細川 浩, 前川 真吾, 小林 茂夫:
    ゼブラフィッシュが持つ自律性体温調節システム,
    第85回日本生理学会大会, 2008年3月.
  3. 杉山 麿人, 細川 浩, 久枝 宏, 小林 茂夫:
    冷刺激が誘発するゼブラフィッシュ稚魚のふるえ ―脊椎動物における恒温性の起源,
    第84回日本生理学会大会, 2007年3月.
  4. 杉山 麿人, 細川 浩, 久枝 宏, 小林 茂夫:
    冷刺激が誘発するゼブラフィッシュ稚魚のふるえ ―脊椎動物の系統発生におけるふるえの進化―,
    第3回環境生理プレコングレス, 2007年3月.
  5. 杉山 麿人, 細川 浩, 久枝 宏, 小林 茂夫:
    冷刺激が誘発するゼブラフィッシュ稚魚のふるえ ―脊椎動物における恒温性の起源か?―,
    体温調節,温度受容研究会, 2007年1月.

学位論文

杉山 麿人,
Studies on Computational Learning via Discretization
PDF

博士論文, 京都大学情報学研究科, 2012年3月.
杉山 麿人,
Cooling-induced Shivering-like Response in Zebrafish
修士論文, 京都大学情報学研究科, 2008年3月.
杉山 麿人,
実数のグレイコード表現とモデル推論を利用した実数値関数の学習,
特別研究報告書(卒業論文),京都大学工学部情報学科, 2006年3月.

統計的有意性を担保するパターンマイニング技術
@article{Sugiyama2017OS,
Author = {杉山, 麿人},
Title = {統計的有意性を担保するパターンマイニング技術},
Journal = {オペレーションズ・リサーチ誌},
Volume = {62},
Number = {4},
Pages = {226--232},
Year = {2017}}
graphkernels: R and Python Packages for Graph Comparison
@article{Sugiyama2017Bioinfo,
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 = {XX},
Number = {XX},
Pages = {XX--XX},
Year = {2017}}
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}}
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}}
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}}