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鹿島 久嗣 (かしま ひさし) の 研究業績
kashi_pong@yahoo.co.jp

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学位論文

ジャーナル論文

  1. Sho Yokoi, Hiroshi Kajino, Hisashi Kashima. Link Prediction in Sparse Networks Using Incidence Matrix Factorization. Journal of Information Processing, Vol.25, pp.477-485, 2017.
  2. 則 のぞみ, 鹿島 久嗣, 山下 和人, 猪飼 宏, 今中 雄一. マルチタスク学習による集中治療室入室患者のリスクモデル構築. 電子情報通信学会論文誌, Vol.J100-D, No.2, pp.194-204, 2017.
  3. Satoshi Oyama, Yukino Baba, Ikki Ohmukai, Hiroaki Dokoshi, Hisashi Kashima. Crowdsourcing Chart Digitizer: Task Design and Quality Control for Making Legacy Open Data Machine-Readable. International Journal of Data Science and Analytics, Vol.2, No.1-2, pp.45-60, 2016.
  4. Yukino Baba, Kei Kinoshita, Hisashi Kashima. Participation Recommendation System for Crowdsourcing Contests. Expert Systems With Applications, Vol.43, pp.174-183, 2016.
  5. Naoki Otani, Yukino Baba, Hisashi Kashima. Quality Control of Crowdsourced Classication Using Hierarchical Class Structures. Expert Systems With Applications, Vol.58, pp.155-163, 2016..
  6. 梶村 俊介, 馬場 雪乃, 梶野 洸, 鹿島 久嗣. 列挙型クラウドソーシングタスクのための品質管理法. 人工知能学会論文誌, Vol.31, No.2, p.K-F79_1-9, 2016.
  7. Kai Morino, Yoshito Hirata, Ryota Tomioka, Hisashi Kashima, Kenji Yamanishi, Norihiro Hayashi, Shin Egawa, Kazuyuki Aihara. Predicting Disease Progression from Short Biomarker Series Using Expert Advice Algorithm. Scientific Reports, Vol.5, No.8953, doi:10.1038/srep08953, 2015.
  8. 則 のぞみ, ボレガラ ダヌシカ, 鹿島 久嗣. 接続行列埋め込みに基づく複数種類の多項関係の同時予測. 人工知能学会論文誌, Vol.30, No.2, pp.459-465, 2015.
  9. Yasunobu Nohara, Eiko Kai, Partha Ghosh, Rafiqul Islam, Ashir Ahmed, Masahiro Kuroda, Sozo Inoue, Tatsuo Hiramatsu, Michio Kimura, Shuji Shimizu, Kunihisa Kobayashi, Yukino Baba, Hisashi Kashima, Koji Tsuda, Masashi Sugiyama, Mathieu Blondel, Naonori Ueda, Masaru Kitsuregawa, Naoki Nakashima. A Health Checkup and Tele-Medical Intervention Program for Preventive Medicine in Developing Countries: A Verification Study. Journal of Medical Internet Research (JMIR), Vol.17, No.1, 2015.
  10. Hiroshi Kajino, Hiromi Arai, Hisashi Kashima. Preserving Worker Privacy in Crowdsourcing. Data Mining and Knowledge Discovery, Vol.27, No.5-6, pp.1314-1335, 2014.
  11. Yukino Baba, Hisashi Kashima, Kei Kinoshita, Goushi Yamaguchi, Yosuke Akiyoshi. Leveraging Non-expert Crowdsourcing Workers for Improper Task Detection in Crowdsourcing Marketplaces. Expert Systems With Applications, Vol.41, No.6, pp.2678-2687, 2014.
  12. 則 のぞみ, ボレガラ ダヌシカ, 鹿島 久嗣. 次元削減による多項関係予測. 人工知能学会論文誌, Vol.29, No.1, pp.168-176, 2014. (人工知能学会論文賞)
  13. Hiroto Saigo, Hisashi Kashima, Koji Tsuda. Fast Iterative Mining Using Sparsity-inducing Loss Functions. IEICE Transaction on Information and Systems, Vol.E96-D, No.8, pp.1766-1773, 2013.
  14. 梶野 洸, 坪井 祐太, 佐藤 一誠, 鹿島 久嗣. エキスパートによる訓練データとクラウドソーシングで作成した訓練データからの教師付き学習. 人工知能学会論文誌, Vol.28, No.3, pp.243-248, 2013.
  15. Xu Sun, Hisashi Kashima, Naonori Ueda. Large-Scale Personalized Human Activity Recognition Using Online Multi-Task Learning. Transactions on Knowledge and Data Engineering, DOI 10.1109/TKDE.2012.246, 2012.
  16. Satoshi Oyama, Kohei Hayashi, Hisashi Kashima. Link Prediction across Time via Cross-temporal Locality Preserving Projections. IEICE Transaction on Information and Systems, Vol.E95-D, No.11, pp.2664-2673, 2012.
  17. Atsuhiro Narita, Kohei Hayashi, Ryota Tomioka, Hisashi Kashima. Tensor Factorization Using Auxiliary Information. Data Mining and Knowledge Discovery, Vol.25, No.2, pp.298-324, 2012.
  18. 林 浩平, 竹之内 高志, 冨岡 亮太, 鹿島 久嗣. 自己計測類似度を用いたマルチタスクガウス過程. 人工知能学会論文誌, Vol.27, No.3, pp.103-110, 2012.
  19. 梶野 洸, 鹿島 久嗣. 凸最適化に基づくクラウドソーシングを用いたマルチタスク学習. 人工知能学会論文誌, Vol.27, No.3, pp.133-142, 2012. (人工知能学会論文賞)
  20. Junichiro Mori, Yuya Kajikawa, Hisashi Kashima, Ichiro Sakata. Machine Learning Approach for Finding Business Partners and Building Reciprocal Relationships. Expert Systems With Applications, Vol.39, No.12, pp.10402-10407, 2012.
  21. 木村 大翼, 久保山 哲二, 渋谷 哲朗, 鹿島 久嗣. 部分パスに基づいた木カーネル. 人工知能学会論文誌, Vol.26, No.3, pp.473-482, 2011.
  22. Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi Sugiyama, Takafumi Kanamori. Statistical Outlier Detection Using Direct Density Ratio Estimation. Knowledge and Information Systems, Vol26, No.2, pp.309-336, 2011.
  23. Reiji Teramoto, Hisashi Kashima. Prediction of Protein-ligand Binding Affinities Using Multiple Instance Learning. Journal of Molecular Graphics and Modelling, Vol.29, No.3, pp.492-497, 2010.
  24. Yosuke Ozawa, Rintaro Saito, Shigeo Fujimori, Hisashi Kashima, Masamichi Ishizaka, Hiroshi Yanagawa, Etsuko Miyamoto-Sato, Masaru Tomita. Protein Complex Prediction via Verifying and Reconstructing the Topology of Domain-domain Interactions. BMC Bioinformatics, Vol. 11, No. 350, 2010.
  25. Hisashi Kashima, Satoshi Oyama, Yoshihiro Yamanishi, Koji Tsuda. Cartesian Kernel: An Efficient Alternative to the Pairwise Kernel. IEICE Transaction on Information and Systems, Vol.E93-D, No.10, pp.2672-2679, 2010.
  26. Masashi Sugiyama, Hirotaka Hachiya, Hisashi Kashima, Tetsuro Morimura. Least Absolute Policy Iteration - A Robust Approach to Value Function Approximation. IEICE Transaction on Information and Systems, Vol.E93-D, No.9, pp.2555-2565, 2010.
  27. 松澤 裕文, 比戸 将平, 井手 剛, 鹿島 久嗣. 教師付き学習を用いた教師無し変化解析手法. 電子情報通信学会論文誌, Vol.J93-D, No.6, pp.816-825, 2010.
  28. Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, Kiyoshi Asai. Conic Programming for Multi-task Learning. IEEE Transactions on Knowledge and Data Engineering, Vol.12, No.7, pp.957-968, 2010.
  29. Tsuyoshi Kato, Kinya Okada, Hisashi Kashima, Masashi Sugiyama. A Transfer Learning Approach and Selective Integration of Multiple Types of Assays for Biological Network Inference. International Journal of Knowledge Discovery in Bioinformatics (IJKDB), Vol.1, No.1, pp.66-80, 2010.
  30. Hiroto Saigo, Masahiro Hattori, Hisashi Kashima, Koji Tsuda. Reaction Graph Kernels Predict EC Numbers of Unknown Enzymatic Reactions in Plant Secondary Metabolism. BMC Bioinfomatics, Vol.11, No.Suppl 1:S31, 2010.
  31. Shohei Hido, Hisashi Kashima, Yutaka Takahashi. Roughly-balanced Bagging for Imbalanced Data. Statistical Analysis and Data Mining, Vol.2, No.5-6, pp.412-426, 2009.
  32. Hisashi Kashima, Yoshihiro Yamanishi, Tsuyoshi Kato, Masashi Sugiyama, Koji Tsuda. Simultaneous Inference of Biological Networks of Multiple Species from Genome-wide Data and Evolutionary Information: A Semi-supervised Approach. Bioinformatics, Vol.25, No.22, pp.2962-2968, 2009.
  33. 坪井 祐太, 森 信介, 鹿島 久嗣, 小田 裕樹, 松本 裕治. 日本語単語分割の分野適応のための部分的アノテーションを用いた条件付確率場の学習. 情報処理学会論文誌, Vol.50, No.6, pp. 1234-1247, 2009. (情報処理学会論文賞)
  34. Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen Bickel, Masashi Sugiyama. Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation. Journal of Information Processing, Vol. 17, pp.138-155, 2009.
  35. Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama. Robust Label Propagation on Multiple Networks. IEEE Transactions on Neural Networks, Vol.20, No.1, pp. 35-44, 2009.
  36. Masashi Sugiyama, Taiji Suzuki, Shinichi Nakajima, Hisashi Kashima, Paul von Bunau, Motoaki Kawanabe. Direct Importance Estimation for Covariate Shift Adaptation. Annals of the Institute of Statistical Mathematics, Vol. 60, No. 4, 2008.
  37. Hisashi Kashima, Shoko Suzuki, Shohei Hido, Yuta Tsuboi, Toshihiro Takahashi, Tsuyoshi Ide, Rikiya Takahashi, Akira Tajima. A Semisupervised Approach Using Spatio-temporal Information for Indoor Location Estimation. In Qiang Yang, Sinno Jialin Pan and Vincent Wenchen Zheng, Estimating Location Using Wi-Fi, IEEE Intelligent Systems, Vol. 23, No. 1, pp. 8-13, Jan/Feb, 2008.
  38. Shoko Suzuki, Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Toshihiro Takahashi, Tsuyoshi Ide, Rikiya Takahashi, Akira Tajima. A Dimensionality Reduction Approach. In Qiang Yang, Sinno Jialin Pan and Vincent Wenchen Zheng, Estimating Location Using Wi-Fi, IEEE Intelligent Systems, Vol. 23, No. 1, pp. 8-13, Jan/Feb, 2008.
  39. Hisashi Kashima. Risk-sensitive Learning via Minimization of Empirical Conditional Value-at-risk. IEICE Transaction on Information and Systems, Vol. E90-D, No. 12, pp. 2043-2052, 2007.
  40. Tetsuji Kuboyama, Hisashi Kashima, Kiyoko F. Aoki-Kinoshita, Kouichi Hirata, Hiroshi Yasuda. A Spectrum Tree Kernel. 人工知能学会論文誌, Vol.22, No.2, pp.140-147, 2007. 2007.
  41. 鹿島 久嗣, 安倍直樹. ネットワーク構造の確率的な時変モデルに基づく教師ありリンク予測. 人工知能学会論文誌, Vol. 22, No. 2, pp.209-217, 2007.
  42. 鹿島 久嗣, 津村 直史, 井手 剛, 野ヶ山 尊秀, 平出 涼, 江藤 博明, 福田 剛志. ネットワークデータを用いた分散システムにおける異常検出. 電子情報通信学会論文誌, Vol. J89-D, No. 2, pp.183-198, 2006.
  43. 鹿島 久嗣, 坂本 比呂志, 小柳 光生. 木構造データに対するカーネル関数の設計と解析. 人工知能学会論文誌, Vol. 21, No. 1, pp.113-121, 2006. (人工知能学会論文賞)
  44. Tetsuo Shibuya, Hisashi Kashima, Akihiko Konagaya. Efficient Filtering Methods for Clustering cDNAs with Spliced Sequence Alignment. Bioinformatics, Vol.20, No.1, pp.29-39, 2004.
  45. Takanori Fukao, Hisashi Kashima, Norihiko Adachi. Decentralized Adaptive Control with Improved Transient Performance. 計測自動制御学会論文集, Vol.35, No.7, pp. 869-878, 1999.

本/解説

  1. Ryota Tomioka, Taiji Suzuki, Kohei Hayashi, Hisashi Kashima. Low-rank Tensor Denoising and Recovery via Convex Optimization. In Regularization, Optimization, Kernels, and Support Vector Machines, 2014.
  2. 鹿島 久嗣. ビッグデータに挑むクラウドソーシング. 電子情報通信学会誌, Vol.97, No.5, pp.364-369, 2014.
  3. 鹿島 久嗣, 馬場 雪乃. ヒューマンコンピュテーション概説. 人工知能学会誌, Vol. 29, No.1, pp.4-11, 2014.
  4. Tetsuo Shibuya, Hisashi Kashima, Jun Sese and Shandar Ahmad (編): Pattern Recognition in Bioinformatics, Proceedings of the 7th IAPR International Conference (PRIB 2012), Lecture Notes in Computer Science, Vol.7632, 2012.
  5. 鹿島 久嗣, 梶野 洸: クラウドソーシングと機械学習, 人工知能学会誌, Vol. 27, No.4, pp.381-388, 2012.
  6. 鹿島 久嗣: グラフとネットワークの構造データマイニング, 電子情報通信学会誌, Vol.93, No.9, pp.797-802, 2010.
  7. Yoshihiro Yamanishi and Hisashi Kashima: Prediction of Compound-protein Interactions with Machine Learning Methods, In Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques, IGI Global, 2010.
  8. Hisashi Kashima, Hiroto Saigo, Masahiro Hattori and Koji Tsuda: Graph Kernels in Chemoinformatics, In Chemoinformatics and Advanced Machine Learning Perspectives: Complex Computational Methods and Collaborative Techniques, IGI Global, 2010.
  9. Hisashi Kashima, Tsuyoshi Ide, Tsuyoshi Kato and Masashi Sugiyama: Recent Advances and Trends in Large-scale Kernel Methods (invited paper), IEICE Transactions on Information and Systems, Vol.92, No.7, pp.1338-1353, 2009.
  10. 鹿島 久嗣: ネットワーク構造予測, 人工知能学会誌, Vol. 22, No. 3, pp.344-351, 2007.
  11. 鹿島 久嗣: 構造データマイニングの手法とバイオインフォマティクスへの応用, ソフトウェア・バイオロジー, Vol.5, pp.21-23, 化学工学会, 2006.
  12. 鹿島 久嗣: カーネル法による構造データの解析, 電子情報通信学会技術研究報告 言語理解とコミュニケーション/パターン認識・メディア理解, Vol.104, No.668, pp.61-66, 2005.
  13. 鹿島 久嗣: カーネル法による構造データマイニング, 情報処理, Vol. 46, No. 1, pp.27-33, 2005.
  14. 鈴木 英之進, 鹿島 久嗣: 特集「最新!データマイニング手法」, 情報処理, Vol. 46, No. 1, pp.2-3, 2005.
  15. Hisashi Kashima, Koji Tsuda and Akihiro Inokuchi: Kernels for Graphs, In Kernel Methods in Computational Biology, MIT Press, pp.155-170, 2004.

特許 (成立したもの)

日本国特許

  1. 比戸 将平, 井手 剛, 鹿島 久嗣, 久保 晴信, 松澤 裕史 (IBM): 変化分析システム、方法及びプログラム, 特許第5159368号.
  2. 鹿島 久嗣 (IBM): 利用者の行動を支援するシステム, 特許第4140915号.
  3. 鹿島 久嗣 (IBM): 分類因子検出装置、分類因子検出方法、プログラム、及び記録媒体, 特許第4107658号.
  4. 江藤 博明, 平出 涼, 鹿島 久嗣, 井手 剛 (IBM): 解析システム、解析方法、解析プログラム、及び記録媒体, 特許第4093483号.
  5. 井手 剛, 依田 邦和, 鹿島 久嗣, 江藤 博明, 平出 涼 (IBM): 異常検出システム及びその方法, 特許第3922375号.
  6. 鹿島 久嗣, 小柳 光生 (IBM): データ処理方法、これを用いた情報処理システム及びプログラム, 特許第3873135号.
  7. 渋谷 哲朗, 鹿島 久嗣 (IBM): データベース検索装置、及びプログラム, 特許第3871301号.
  8. 鹿島 久嗣, 梶永 泰正 (IBM): 「情報処理方法、情報処理システムおよび記録媒体, 特許3579828号.

米国特許

  1. Hisashi Kashima, Kazutaka Yamasaki (IBM): Method for Regression from Interval Target Values by Alternating Linear Gaussian and Expectation-Maximization, U.S.Patent:8140447.
  2. Shohei Hido, Tsuyoshi Ide, Hisashi Kashima, Shoko Suzuki, Akira Tajima, Rikiya Takahashi, Toshihiro Takahashi, Yuta Tsuboi (IBM): A Location Estimation Method Using Label Propagation, U.S.Patent:8138974.
  3. Hisashi Kashima (IBM): Method and System for L1-based Robust Distribution Clustering of Multinomial Distributions, U.S.Patent:7996340.
  4. Hiroaki Etoh, Ryo Hirade, Hisashi Kashima, Tsuyoshi Ide (IBM): Computer Operation Analysis, U.S.Patent:7493361.
  5. Hisashi Kashima (IBM): System for Supporting User's Behavior, U.S.Patent: 7467120.
  6. Tsuyoshi Ide, Kunikazu Yoda, Hisashi Kashima (IBM), Hiroaki Etoh, Ryo Hirade: Anomaly Detection, U.S.Patent: 7346803.
  7. Akihiro Inokuchi, Hisashi Kashima (IBM): Classification Factor Detection, U.S.Patent: 7337186.
  8. Hisashi Kashima, Yasumasa Kajinaga (IBM): Auction Method and Auction System, and StorageMmedium Therefor, U.S.Patent: 7231365.
  9. Hisashi Kashima, Teruo Koyanagi (IBM): Classification Method of Labeled Ordered Trees Using Support Vector Machines, U.S.Patent: 7130,833.
  10. Tetsuo Shibuya, Hisashi Kashima (IBM): Database Search Device, Database Search System, Database Search Method, Program and Storage Medium, U.S.Patent: 6928437.

国際会議/ワークショップ論文

  1. Jiyi Li, Yukino Baba, Hisashi Kashima. Hyper Questions: Unsupervised Targeting of a Few Experts in Crowdsourcing. In Proceeding of the 26th ACM International Conference on Information and Knowledge Management (CIKM), 2017.
  2. Hirotaka Akita, Yukino Baba, Hisashi Kashima, Atsuto Seko. Atomic Distance Kernel for Material Property Prediction. In Proceeding of the 24th International Conference on Neural Information Processing (ICONIP), 2017.
  3. Kosuke Yoshimura, Yukino Baba, Hisashi Kashima. Quality Control for Crowdsourced Multi-Label Classification using RAkEL. In Proceeding of the 24th International Conference on Neural Information Processing (ICONIP), 2017.
  4. Jiyi Li, Tomohiro Arai, Yukino Baba, Hisashi Kashima, Shotaro Miwa. Distributed Multi-task Learning for Sensor Network. In Proceeding of the European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2017.
  5. Guoxi Zhang, Tomoharu Iwata, Hisashi Kashima. Robust Multi-view Topic Modeling by Incorporating Detecting Anomalies. In Proceeding of the European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2017.
  6. Jiuding Duan, Jiyi Li, Yukino Baba, Hisashi Kashima. A Generalized Model for Multidimensional Intransitivity. In Proceedings of the 21st Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2017.
  7. Takeru Sunahase, Yukino Baba, Hisashi Kashima Pairwise HITS: Quality Estimation from Pairwise Comparisons in Creator-Evaluator Crowdsourcing Process. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), 2017.
  8. Nozomi Nori, Hisashi Kashima, Kazuto Yamashita, Susumu Kunisawa, Yuichi Imanaka. Learning Implicit Tasks for Patient-Specific Risk Modeling in ICU. In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), 2017.
  9. Yuji Horiguchi, Yukino Baba, Hisashi Kashima, Masahito Suzuki, Hiroki Kayahara, Jun Maeno. Predicting Fuel Consumption and Flight Delays for Low-cost Airlines. In Proceedings of the 29th Conference on Innovative Applications of Artificial Intelligence (IAAI), 2017.
  10. Kaito Fujii, Hisashi Kashima. Budgeted Stream-based Active Learning via Adaptive Submodular Maximization. In Advances in Neural Information Processing Systems (NIPS) 29, 2016.
  11. Patrick Joerger, Yukino Baba, Hisashi Kashima. Learning to Enumerate. In Proceedings of the 25th International Conference on Artificial Neural Networks (ICANN), pp.XX-XX, Barcelona, Spain, 2016.
  12. Sho Yokoi, Hiroshi Kajino, Hisashi Kashima. Link Prediction by Incidence Matrix Factorization. In Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI), pp.XX-XX, The Hague, Holland, 2016.
  13. Ryusuke Takahama, Toshihiro Kamishima, Hisashi Kashima. Progressive Comparison for Ranking Estimation. In Proc. 25th International Joint Conference on Artificial Intelligence (IJCAI), pp.XX-XX, New York, NY, USA, 2016.
  14. Naoki Otani, Yukino Baba, Hisashi Kashima. Quality Control for Crowdsourced Hierarchical Classification. In Proceedings of the 2015 IEEE International Conference on Data Mining (ICDM), pp.937-942, Atlantic City, NJ, USA, 2015.
  15. Satoshi Oyama, Yukino Baba, Ikki Ohmukai, Hiroaki Dokoshi, Hisashi Kashima. From One Star to Three Stars: Upgrading Legacy Open Data Using Crowdsourcing. In Proceedings of the 2015 International Conference on Data Science and Advanced Analytics (DSAA), pp.1-9, Paris, France, 2015.
  16. Junpei Komiyama, Junya Honda, Hisashi Kashima, Hiroshi Nakagawa. Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem. In Proceedings of the 28nd Annual Conference on Learning Theory (COLT), pp.1141-1154, Paris, France, 2015.
  17. Jiuding Duan, Atsuto Seko, Hisashi Kashima. Quantum Energy Prediction Using Graph Kernel. In Proceedings of the 2015 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC), pp.1651-1656, Hong Kong, China, 2015.
  18. Yukino Baba, Hisashi Kashima, Yasunobu Nohara, Eiko Kai, Partha Ghosh, Rafiqul Islam, Ashir Ahmed, Masahiro Kuroda, Sozo Inoue, Tatsuo Hiramatsu, Michio Kimura, Shuji Shimizu, Kunihisa Kobayashi, Koji Tsuda, Masashi Sugiyama, Mathieu Blondel, Naonori Ueda, Masaru Kitsuregawa, Naoki Nakashima. Predictive Approaches for Low-cost Preventive Medicine Program in Developing Countries. In Proc. 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2015.
  19. Nozomi Nori, Hisashi Kashima, Kazuto Yamashita, Hiroshi Ikai, Yuichi Imanaka. Simultaneous Modeling of Multiple Diseases for Mortality Prediction in Acute Hospital Care. In Proc. 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2015.
  20. Shunsuke Kajimura, Yukino Baba, Hiroshi Kajino, Hisashi Kashima. Quality Control for Crowdsourced POI Collection. In Proc. 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2015.
  21. Yukino Baba, Nozomi Nori, Shigeru Saito, Hisashi Kashima. Crowdsourced Data Analytics: A Case Study of Predictive Modeling Competition. In Proc. 2014 International Conference on Data Science and Advanced Analytics (DSAA), pp.XX-XX, Shanghai, China, 2014.
  22. Toshihiro Watanabe, Hisashi Kashima. A Label Completion Approach to Crowd Aproximation. In Proc. 21st International Conference on Neural Information Processing (ICONIP), pp.377-385, Kuching, Sarawak, Malaysia, 2014.
  23. Ryoma Kawajiri, Masamichi Shimosaka, Hisashi Kashima. Steered Crowdsensing: Incentive Design towards Quality-Oriented Place-Centric Crowdsensing. In Proc. ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), pp.XX-XX, Seattle, Washingron, USA, 2014.
  24. Hiroshi Kajino, Yukino Baba, Hisashi Kashima. Instance-privacy Preserving Crowdsourcing. In Proc. 2nd Conference on Human Computation and Crowdsourcing (HCOMP), Pittsburgh, USA, 2014.
  25. Issei Sato, Hisashi Kashima, Hiroshi Nakagawa. Latent Confusion Analysis by Normalized Gamma Construction. In Proc. 31th International Conference on Machine Learning (ICML), Beijing, China, 2014.
  26. Toshiko Matsui, Yukino Baba, Toshihiro Kamishima and Hisashi Kashima. Crowdordering. In Proc. 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp.336-347, Tainan, Taiwan, 2014.
  27. Jingjing Wang, Satoshi Oyama, Masahito Kurihara and HisashiKashima. Learning an Accurate Entity Resolution Model from Crowdsourced Labels. In Proc. the 8th International Conference on Ubiquitous Information Management and Communication (ICUIMC/IMCOM), Siem Reap, Cambodia, 2014.
  28. Yukino Baba and Hisashi Kashima. Statistical Quality Estimation for General Crowdsourcing Tasks, In Proc. 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp.554-562, Chicago, USA, 2013.
  29. Satoshi Oyama, Yukino Baba, Yuko Sakurai and Hisashi Kashima. Utilizing Workers' Self-reported Confidence to Integrate Multiple Crowdsourced Labels. In Proc. 23rd International Joint Conference on Artificial Intelligence (IJCAI), pp.2554-2560, Beijing, China, 2013.
  30. Hiroshi Kajino, Yuta Tsuboi and Hisashi Kashima: Clustering Crowds, In Proc. 27th AAAI Conference on Artificial Intelligence (AAAI), pp.XX-XX, Bellevue, Washington, USA, 2013.
  31. Yukino Baba, Hisashi Kashima, Kei Kinoshita, Goushi Yamaguchi, Yosuke Akiyoshi: Leveraging Crowdsourcing to Detect Improper Tasks in Crowdsourcing Marketplaces, In Proc. 25th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI), pp.XX-XX, Bellevue, Washington, USA, 2013.
  32. Yoshifumi Aimoto and Hisashi Kashima: Matrix Factorization with Aggregated Observations, In Proc. 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp.XX-XX, Gold Coast, Australia, 2013. (Best Student Paper Runner Up Award)
  33. Shohei Hido and Hisashi Kashima: Hash-based Structural Similarity for Semi-supervised Learning on Attribute Graphs, In Proc. 23rd International Conference on Pattern Recognition (ICPR), Tsukuba, Japan, 2012.
  34. Michael E. Houle, Hisashi Kashima and Michael Nett: Fast Similarity Computation in Factorized Tensors, In Proc. 5th International Conference on Similarity Search and Applications (SISAP), pp.226-239, Toronto, Canada, 2012.
  35. Daisuke Kimura and Hisashi Kashima: Fast Computation of Subpath Kernel for Trees, In Proc. 29th International Conference on Machine Learning (ICML), pp.XXX-XXX, Edinburgh, Scotland, 2012.
  36. Hiroshi Kajino, Yuta Tsuboi, Issei Sato and Hisashi Kashima: Learning from Crowds and Experts, In Proc. 4th Human Computation Workshop (HCOMP), pp.107-113, Toronto, Ontario, Canada, 2012.
  37. Hiroshi Kajino, Yuta Tsuboi and Hisashi Kashima: A Convex Formulation for Learning from Crowds, In Proc. 26th AAAI Conference on Artificial Intelligence (AAAI), pp.73-79, Toronto, Ontario, Canada, 2012.
  38. Nozomi Nori, Danushka Bollegara and Hisashi Kashima: Multinomial Relation Prediction in Social Data: A Dimension Reduction Approach, In Proc. 26th AAAI Conference on Artificial Intelligence (AAAI), pp.115-121, Toronto, Ontario, Canada, 2012.
  39. Satoshi Oyama, Kohei Hayashi and Hisashi Kashima: Cross-temporal Link Prediction, In Proc. 11th International Conference on Data Mining (ICDM), pp.1188-1193, Vancouver, Canada, 2011.
  40. Xu Sun, Hisashi Kashima, Ryota Tomioka and Naonori Ueda: A New Multi-task Learning Method for Personalized Activity Recognition, In Proc. 11th International Conference on Data Mining (ICDM), pp.1218-1223, Vancouver, Canada, 2011.
  41. Ryota Tomioka, Taiji Suzuki, Kohei Hayashi and Hisashi Kashima: Statistical Performance of Convex Tensor Decomposition, In Proc. 25th Annual Conference on Neural Information Processing Systems (NIPS), Granada, Spain, 2011.
  42. Atsuhiro Narita, Kohei Hayashi, Ryota Tomioka and Hisashi Kashima: Tensor Factorization Using Auxiliary Information, In Proc. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp.501-516, Athens, Greece, 2011. (Best Student Paper Award)
  43. Yuta Tsuboi, Yuya Unno, Hisashi Kashima and Naoaki Okazaki: Fast Newton-CG Method for Batch Learning of Conditional Random Fields, In Proc. 25th AAAI Conference on Artificial Intelligence (AAAI), pp.489-494, San Francisco, California, USA, 2011.
  44. Daisuke Kimura, Tetsuji Kuboyama, Tetsuo Shibuya and Hisashi Kashima: A Subpath Kernel for Rooted Unordered Trees, In Proc. 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp.62-74, Shenzeng, China, 2011.
  45. Xu Sun, Hisashi Kashima, Ryota Tomioka and Naonori Ueda: Large Scale Real-life Action Recognition Using Conditional Random Fields with Stochastic Training, In Proc. 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp.222-233, Shenzeng, China, 2011.
  46. Junichiro Mori, Yuya Kajikawa, Ichiro Sakata and Hisashi Kashima: Predicting Customer-supplier Relationships Using Network-based Features, In Proc. IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), pp.1916-1920, Macau, China, 2010.
  47. Xu Sun, Hisashi Kashima, Takuya Matsuzaki and Naonori Ueda: A Robust, Accurate, and Fast Stochastic Gradient Training Method for Modeling Latent-Information in Data, In Proc. 10th International Conference on Data Mining (ICDM), Sydney, Australia, 2010.
  48. Rudy Raymond and Hisashi Kashima: Fast and Scalable Algorithms for Semi-supervised Link Prediction on Static and Dynamic Graphs, In Proc. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), pp.131-147, Barcelona, Spain, 2010.
  49. Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya and Toshiyuki Tanaka: Return Density Approximation for Reinforcement Learning, In Proc. 26th Conference on Uncertainty in Artificial Intelligence (UAI), Catalina Island, California, USA, 2010.
  50. Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama and Hisashi Kashima: A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices, In Proc. 26th International Conference on Machine Learning (ICML), pp.1087-1094, Haifa, Israel, 2010.
  51. Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya and Toshiyuki Tanaka: Nonparametric Return Density Estimation Reinforcement Learning, In Proc. 26th International Conference on Machine Learning (ICML), pp.799-806, Haifa, Israel, 2010.
  52. Mutsumi Fukuzaki, Mio Seki, Hisashi Kashima and Jun Sese: Finding Itemset-Sharing Patterns in a Large Itemset-Associated Graph, In Proc. 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp.147-159, Hyderabad, India, 2010.
  53. Junichiro Mori, Yuya Kajikawa and Hisashi Kashima: Finding Your Business Partners by Using Machine Learning, In Proc. 19th International Conference on Management of Technology (IAMOT), Cairo, Egypt, 2010.
  54. Hisashi Kashima, Shohei Hido, Yuta Tsuboi, Akira Tajima, Takeshi Ueno, Naoki Shibata, Ichiro Sakata and Toshiya Watanabe: Predictive Modeling of Patent Quality by Using Text Mining (スライド), In Proc. 19th International Conference on Management of Technology (IAMOT), Cairo, Egypt, 2010.
  55. Hiroto Saigo, Masahiro Hattori, Hisashi Kashima and Koji Tsuda: Reaction Graph Kernels Predict EC Numbers of Unknown Enzymatic Reactions in Plant Secondary Metabolism, In Proc. 8th Asia Pacific Bioinformatics Conference (APBC2010), Bangalore, India, 2010.
  56. Shohei Hido and Hisashi Kashima: A Linear-time Graph Kernel, In Proc. 9th IEEE International Conference on Data Mining (ICDM), pp.179-188, Miami, Florida, USA, 2009.
  57. Mutsumi Fukuzaki, Mio Seki, Hisashi Kashima and Jun Sese: Side Effect Prediction Using Cooperative Pathways. In Proc. IEEE International Conference on Bioinformatics and Biomedicine 2009 (IEEE BIBM), pp.142-147, Washington D.C., USA, 2009.
  58. Masashi Sugiyama, Hirotaka Hachiya, Hisashi Kashima and Tetsuro Morimura: Least Absolute Policy Iteration for Robust Value Function Approximation, 2009 IEEE International Conference on Robotics and Automation (ICRA), pp.2904-2909, Kobe, Japan, 2009.
  59. Hisashi Kashima, Satoshi Oyama, Yoshihiro Yamanishi and Koji Tsuda: On Pairwise Kernels: An Efficient Alternative and Generalization Analysis, In Proc. 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp.1030-1037, Bangkok, Thailand, 2009.
  60. Hisashi Kashima, Tsuyoshi Kato, Yoshihiro Yamanishi, Masashi Sugiyama and Koji Tsuda: Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction, In Proc. 2009 SIAM Conference on Data Mining (SDM), pp. 1099-1110, Sparks, Nevada, 2009.
  61. Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi Sugiyama and Takafumi Kanamori: Inlier-based Outlier Detection via Direct Density Ratio Estimation, In Proc. 8th IEEE International Conference on Data Mining (ICDM), pp.223-232, Pisa, Italy, 2008.
  62. Hisashi Kashima, Jianying Hu, Bonnie Ray and Moninder Singh: K-means Clustering of Proportional Data Using L1 Distance (スライド), In Proc. 19th International Conference on Pattern Recognition (ICPR), Tampa, Florida, USA, 2008.
  63. Yuta Tsuboi and Hisashi Kashima: A New Objective Function for Sequence Segmentation, In Proc. 19th International Conference on Pattern Recognition (ICPR), Tampa, Florida, USA, 2008.
  64. Hisashi Kashima, Kazutaka Yamasaki, Hiroto Saigo and Akihiro Inokuchi: Regression with Interval Output Values (スライド), In Proc. 19th International Conference on Pattern Recognition (ICPR), Tampa, Florida, USA, 2008.
  65. Yuta Tsuboi, Hisashi Kashima, Shinsuke Mori, Hiroki Oda and Yuji Matsumoto: Training Conditional Random Fields Using Incomplete Annotations (スライド), In Proc. 22nd International Conference on Computational Linguistics (COLING), pp.897-904, Manchester, UK, 2008.
  66. Shohei Hido, Tsuyoshi Ide, Hisashi Kashima, Harunobu Kubo and Hirofumi Matsuzawa: Unsupervised Change Analysis Using Supervised Learning, In Proc. 12th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp.148-159, Osaka, Japan, 2008.
  67. Tsuyoshi Kato, Hisashi Kashima and Masashi Sugiyama: Integration of Multiple Networks for Robust Label Propagation, In Proc. 2008 SIAM International Conference on Data Mining (SDM), pp.716-726, Atlanta, Georgia, USA, 2008.
  68. Shohei Hido and Hisashi Kashima: Roughly Balanced Bagging for Imbalanced Data, In Proc. 2008 SIAM International Conference on Data Mining (SDM), pp.143-152, Atlanta, Georgia, USA, 2008.
  69. Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen Bickel and Masashi Sugiyama: Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptationスライド), In Proc. 2008 SIAM International Conference on Data Mining (SDM), pp.443-454, Atlanta, Georgia, USA, 2008.
  70. Hisashi Kashima, Shoko Suzuki, Shohei Hido, Yuta Tsuboi, Toshihiro Takahashi, Tsuyoshi Ide, Rikiya Takahashi and Akira Tajima: A Semi-supervised Approach to Indoor Location Estimation (スライド), In IEEE ICDM Data Mining Contest, Omaha, Nebraska, USA, 2007 (15チーム中 1位)
  71. Shoko Suzuki, Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Toshihiro Takahashi, Tsuyoshi Ide, Rikiya Takahashi and Akira Tajima: A Semi-supervised Approach to Transferring the Learned Knowledge for Indoor Location Estimation, In IEEE ICDM Data Mining Contest, Omaha, Nebraska, USA, 2007 (17チーム中 3位)
  72. Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashima, Paul von Bunau and Motoaki Kawanabe: Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation, In Proc. 21st Annual Conference on Neural Information Processing Systems (NIPS), Vancouver, B.C., Canada, 2007.
  73. Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama and Kiyoshi Asai: Multi-task Learning via Conic Programming, In Proc. 21st Annual Conference on Neural Information Processing Systems (NIPS), Vancouver, B.C., Canada, 2007.
  74. Tetsuji Kuboyama, Kouichi Hirata, Kiyoko F. Aoki-Kinoshita, Hisashi Kashima and Hiroshi Yasuda: A Gram Distribution Kernel Applied to Glycan Classification and Motif Extraction, In Proc. 17th International Conference on Genome Informatics (GIW), Yokohama, Japan, 2006.
  75. Hisashi Kashima and Naoki Abe: A Parameterized Probabilistic Model of Network Evolution for Supervised Link Prediction, In Proc. 6th IEEE International Conference on Data Mining (ICDM), pp.340-349, Hong Kong, 2006.
  76. Tetsuji Kuboyama, Hisashi Kashima, Kiyoko F. Aoki-Kinoshita, Koichi Hirata and Hiroshi Yasuda: A Spectrum Tree Kernel, In Proc. The International Workshop on Data-Mining and Statistical Science (DMSS), Sapporo, Japan, 2006.
  77. Tetsuji Kuboyama, Kilho Shin and Hisashi Kashima: Flexible Tree Kernels Based on Counting the Number of Tree Mappings, In Proc. Workshop on Mining and Learning (held with ECML/PKDD 2006), Berlin, Germany, 2006.
  78. Hisashi Kashima: Risk-Sensitive Learning via Expected Shortfall Minimization , In Proc. 2006 SIAM Conference on Data Mining (SDM), pp.529-533, Bethesda, Maryland, USA, 2006. (full paper version)
  79. Hisashi Kashima, Tadashi Tsumura, Tsuyoshi Ide, Takahide Nogayama, Ryo Hirade, Hiroaki Etoh and Takeshi Fukuda: Network-Based Problem Detection for Distributed Systems, In Proc. 21st International Conference on Data Engineering (ICDE), pp.978-989, Tokyo, Japan, 2005.
  80. Tsuyoshi Ide and Hisashi Kashima: Eigenspace-based Anomaly Detection in Computer Systems, In Proc. 10th ACM SIGKDD Conference (KDD), pp.440-449, Seattle, Washington, USA, 2004.
  81. Hisashi Kashima and Yuta Tsuboi: Kernel-Based Discriminative Learning Algorithms for Labeling Sequences, Trees and Graphs, In Proc. 21st International Conference on Machine Learning (ICML), pp.58-65, Banff, Alberta, Canada, 2004.
  82. Makoto Kano, Hisashi Kashima, Tetsuo Shibuya, Kaori Ide, Aiko Kashihara, Noriko Nakagawa, Mariko Hatakeyama, Seiki Kuramitsu and Akihiko Konagaya: A Method for Normalization of Gene Expression Data, In Proc. Genome Informatics Workshop (GIW), Yokohama, Japan, 2003.
  83. Akihiro Inokuchi and Hisashi Kashima: Mining Significant Pairs of Patterns from Graph Structures with Class Labels, In Proc. 3rd IEEE International Conference on Data Mining (ICDM), pp.83-90, Melbourne, Florida, USA, 2003.
  84. Hisashi Kashima , Koji Tsuda and Akihiro Inokuchi: Marginalized Kernels Between Labeled Graphs, In Proc. 20th International Conference on Machine Learning (ICML), pp.321-328, Washington DC, USA, 2003.
  85. Hisashi Kashima and Akihiro Inokuchi: Kernels for Graph Classification, In Proc. 1st ICDM Workshop on Active Mining (AM), Maebashi, Japan, 2002.
  86. Hisashi Kashima and Teruo Koyanagi: Kernels for Semi-Structured Data, In Proc. 19th International Conference on Machine Learning (ICML), pp.291-298, Sydney, Australia, 2002.
  87. Takanori Fukao, Hisashi Kashima and Norihiko Adachi: Decentralized Adaptive Control of Dynamic Interconnected Systems with Improved Performance, In Proc. 8th IFAC Symposium on Large Scale Systems: Theory and Applications, pp. 138-143, 1998.
  88. Takanori Fukao, Hisashi Kashima and Norihiko Adachi: Robust Adaptive Control of Large-Scale Systems with Unmodeled Dynamic Interconnections, Proc. of the 2nd Asian Control Conference, Vol 2, pp. 5-8, 1997.

国内の会議/研究会論文

  1. 馬場 雪乃, 鹿島 久嗣, 木下 慶, 山口 豪志, 秋好 陽介: 機械学習による不適切なクラウドソーシングタスクの検出 第5回データ工学と情報マネジメントに関するフォーラム (DEIM2013), 2013. (優秀論文賞)
  2. 梶野 洸, 荒井 ひろみ, 鹿島 久嗣: クラウドソーシングにおけるワーカープライバシを保護した品質管理 第5回データ工学と情報マネジメントに関するフォーラム (DEIM2013), 2013. (筆頭著者による学生プレゼンテーション賞)
  3. 則 のぞみ, ボレガラ ダヌシカ, 鹿島 久嗣: ソーシャルWebサービスにおけるユーザ行動予測:次元削減アプローチ 人工知能学会全国大会 (第26回), 2012.
  4. 梶野 洸, 坪井 祐太, 佐藤 一誠, 鹿島 久嗣: 既存の教師データとクラウドソーシングを併用した教師付き学習 人工知能学会全国大会 (第26回), 2012.
  5. 木村 大翼, 鹿島 久嗣: 木構造の垂直方向の構造に基づいた線形時間木カーネル 人工知能学会全国大会 (第26回), 2012.
  6. 梶野 洸, 鹿島 久嗣: クラウドソーシングを用いた教師付き学習の凸最適化による定式化 第14回 情報論的学習理論ワークショップ (IBIS 2011), 信学技報, vol. 111, no. 275, IBISML2011-76, pp. 231-236, 2011. (筆頭著者によるポスター奨励賞)
  7. 木村 大翼, 鹿島 久嗣: 部分パスに基づいた線形時間木カーネル 第14回 情報論的学習理論ワークショップ (IBIS 2011), 信学技報, vol. 111, no. 275, IBISML2011-85, pp. 291-296, 2011.
  8. 林 浩平, 竹之内高志, 冨岡 亮太, 鹿島 久嗣: カーネル法に基づく行列あるいはテンソル補完 第14回 情報論的学習理論ワークショップ (IBIS 2011), 信学技報, vol. 111, no. 275, IBISML2011-53, pp. 71-77, 2011. (筆頭著者によるHonorable Mention)
  9. 成田 敦博, 林 浩平, 冨岡 亮太, 鹿島 久嗣: 補助情報を用いたテンソル分解 第4回 電子情報通信学会 情報論的学習理論と機械学習研究会(IBISML), 信学技報, Vol.110, No.476, IBISML2010-124, pp.139-146, 2011.
  10. 諏訪 恭平, 冨岡 亮太, 矢入 健久, 鹿島 久嗣: 複数情報源に対する主成分分析 (スライド) 第4回 電子情報通信学会 情報論的学習理論と機械学習研究会(IBISML), 信学技報, Vol.110, No.476, IBISML2010-125, pp.147-152, 2011.
  11. 鹿島 久嗣, 山西 芳裕, 加藤 毅, 杉山 将, 津田 宏治: 複数生物種ネットワークの同時予測:半教師つき学習によるアプローチ (スライド), 第21回 情報処理学会 バイオ情報学研究会 (SIG-BIO), Vol.2010-BIO-21, No.19, 2010. (情報処理学会山下記念研究賞)
  12. 鹿島 久嗣, 加藤 毅, 山西 芳裕, 杉山 将, 津田 宏治: リンク伝播法: リンク予測のための半教師付き学習法 (スライド), 第73回 人工知能学会 人工知能基本問題研究会 (SIG-FPAI), 2009.
  13. 福崎 睦美, 関 美緒, 鹿島 久嗣, 瀬々 潤: アイテム集合を付与したグラフからの頻出グラフ発見, DEIMフォーラム2009, 2009.
  14. 鹿島 久嗣, 小山 聡, 山西 芳裕, 津田 宏治: 高速なペアワイズカーネルの提案と汎化誤差解析について (スライド), 第11回 情報論的学習理論ワークショップ (IBIS 2008), 2008.
  15. 坪井 祐太, 鹿島 久嗣, 森 信介, 小田 裕樹, 松本 裕治: 部分的かつ曖昧なラベル付き構造データからのマルコフ条件付確率場の学習 (スライド), 情報処理学会 自然言語処理研究会(NL-182), 2007.
  16. 比戸 将平,坪井 祐太,鹿島 久嗣,杉山 将: Ma href="http://2boy.org/~yuta/publications/ibis2007.pdf">密度比推定を用いた特異点検出手法, 第10回 情報論的学習理論ワークショップ (IBIS 2007), 2007.
  17. Tsuyoshi Kato,Hisashi Kashima, Masashi Sugiyama: Probabilistic Label Propagation on Multiple Networks, 第10回 情報論的学習理論ワークショップ (IBIS 2007) , 2007.
  18. 鹿島 久嗣, 山崎 一孝, 西郷 浩人, 猪口 明博: 目的変数が範囲で与えられる回帰問題に対するEM法, The International Workshop on Data-Mining and Statistical Science (DMSS2007)スライド), 2007. (人工知能学会研究会優秀賞)
  19. Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashima, Paul von Bunau, Motoaki Kawanabe: Kullback-Leibler importance estimation procedure for covariate shift adaptation, The International Workshop on Data-Mining and Statistical Science (DMSS2007) , 2007.
  20. Tsuyoshi Ide and Hisashi Kashima: Effective Dimension in Anomaly Detection: Its Application to Computer Systems, New Frontiers in Artificial Intelligence (Post-proceedings of the Eighteenth Annual Conference of Japanese Society of Artificial Intelligence), Lecture Notes in Artificial Intelligence, Vol. 3609, pp. 189-204, 2007.
  21. Tetsuji Kuboyama, Koichi Hirata, Hisashi Kashima and Kiyoko F. Aoki-Kinoshita: The Gram Distribution Kernel: A Tree Kernel for Glycan Classification, 人工知能学会 第63回 人工知能基本問題研究会 (SIG-FPAI), 2006.
  22. 久保山 哲二, 申 吉浩, 鹿島 久嗣, 平田 耕一: 共通構造の数え上げによる半構造データカーネルの設計, 電子情報通信学会 第17回データ工学ワークショップ (DEWS2006), 2006
  23. 鹿島 久嗣: リスク回避型学習, 第8回 情報論的学習理論ワークショップ (IBIS 2005), 2005.
  24. 坪井 祐太, 鹿島 久嗣: 構造データのラベル付け学習モデルの設計,(スライド第8回 情報論的学習理論ワークショップ (IBIS 2005), 2005.
  25. 鹿島 久嗣, 坪井 祐太: 構造化データのラベル付け学習とカーネル法(スライド), 構造化データの機械学習研究会(MOST), 2005.
  26. 鹿島 久嗣, 坪井 祐太: カーネル法に基づく構造データのラベリング学習アルゴリズム, 電子情報通信学会 人工知能と知識処理研究会(AI), 2004.
  27. 井手 剛, 鹿島 久嗣: 固有空間におけるコンピュータシステムの障害検知, 人工知能学会全国大会, 2004. (筆頭著者による人工知能学会全国大会優秀賞)
  28. 猪口 明博, 鹿島 久嗣: クラスラベル付きグラフデータからの有用なパターンペア発見, 人工知能学会 知識ベースシステム研究会, SIG-KBS, 2004. (人工知能学会研究会優秀賞)
  29. Tetsuo Shibuya, Christian Schoenbach, Hisashi Kashima and Akihiko Konagaya: Accurate cDNA Clustering Algorithm based on Spliced Sequence Alignment, 電子情報通信学会コンピュテーション研究会, COMP-2002-9-14, 17-24, 2002.
  30. 鹿島 久嗣, 小柳 光生: 半構造データに対するサポートベクターマシンの適用, 人工知能学会 人工知能基礎論研究会, SIG-FAI-A104, 2002.
  31. 鹿島 久嗣: 確率的ブーリアンネットワークを用いた遺伝子ネットワークの同定, 人工知能学会 分子生物情報研究会, 2001.
  32. 鹿島 久嗣: 乗算型学習アルゴリズムを用いた属性選択, 人工知能学会全国大会, 2001.
  33. Hisashi Kashima and Yasumasa Kajinaga: Optimal Winner Determination Algorithms for E-procurement Auction,電子情報通信学会 コンピュテーション研究会, COMP-2000-57-63, 17-23, 2000.

セミナー等での講演

  1. 鹿島 久嗣, 小山 聡: 「クラウドソーシングとビッグデータ解析」, 情報処理学会研究報告 CVIM(コンピュータビジョンとイメージメディア), 2014/9/2.
  2. 鹿島 久嗣, 小山 聡: 「クラウドソーシングで挑むビッグデータ解析」(スライド), クラウドソーシングとソーシャルメディア, 情報処理学会 連続セミナー ビッグデータの深化と真価 〜最新技術から活用事例まで〜, 2013/12/16.
  3. 鹿島 久嗣: 「機械学習とクラウドソーシング - 機械の知と人間の知の融合」(スライド), 情報論的学習理論と機械学習研究会 (IBISML) チュートリアル, 2013/11/11.
  4. 鹿島 久嗣: 「ネットワーク分析のための機械学習〜標準タスクと基本モデル〜」(スライド), ビッグデータに立ち向かう機械学習, 情報処理学会 連続セミナー ビッグデータとスマートな社会, 2012/11/19.
  5. 鹿島 久嗣: 「ネットワークと機械学習」スライド), 言語処理学会第18回年次大会(NLP2012), 2012/3/13.
  6. 鹿島 久嗣: 「広がる機械学習の応用」(スライド), 情報処理学会東海支部 講演会, 2012/1/10.
  7. 鹿島 久嗣: 「特許の質の予測:機械学習とテキストマイニングによるアプローチ」(スライド), 「イノベーションと知財マネジメント」公開セミナー, 2010/3/5.
  8. 鹿島 久嗣: 「機械学習とその応用」(スライド1, スライド2), 京都大学 工学部情報学科, 2009/5/15.
  9. 鹿島 久嗣: 「生体ネットワーク予測の機械学習」(スライド), 日本バイオインフォマティクス学会 バイオインフォマティクス夏の学校2007, 2007/8/7.
  10. Hisashi Kashima: 「Methods for Predicting Network Structures」(スライド), The International Workshop on Data-Mining and Statistical Science (DMSS2006), 2006/9/26.
  11. 鹿島 久嗣: 「ネットワーク構造解析 - 機械学習によるアプローチ -」(スライド), 人工知能学会 第63回 人工知能基本問題研究会 (SIG-FPAI), 2006/9/8.
  12. 鹿島 久嗣, 坪井 祐太, 工藤 拓: 「言語処理における識別モデルの発展 -- HMMからCRFまで --」(スライド), 言語処理学会第12回年次大会(NLP2006), 2006/3/13.
  13. 鹿島 久嗣, 坂本 比呂志: 「木構造データに対するカーネル関数の設計と解析」(スライド), 木とカーネルのセミナー, 九州工業大学, 2006/1/13.
  14. 鹿島 久嗣: 「構造データマイニングの手法とバイオインフォマティクスへの応用」, シンポジウム:産業応用に向けたバイオインフォマティクス, 化学工学会 第37回秋期大会, 2005/9/17.
  15. 鹿島 久嗣: 「カーネル法による構造データの解析」(スライド), 電子情報通信学会パターン認識・メディア理解研究会, 国立情報学研究所(NII), 2005/2/25.
  16. 鹿島 久嗣: 「A Kernel-based Approach to Sequence Labeling Problems」スライド) バイオインフォマティクスセミナー, 京都大学科学研究所バイオインフォマティクスセンター, 2004/9/6.
  17. 鹿島 久嗣: 「構造をもつインスタンスに対するカーネル関数のアルゴリズム設計」, 生命情報科学特別講義, 産業技術総合研究所 生命情報科学研究センター(CBRC), 2003/1/8.

翻訳

  1. 元田 浩, 栗田 多喜夫, 樋口 知之, 松本 裕治, 村田 昇(監訳), Christopher M. Bishop(著): パターン認識と機械学習 - ベイズ理論による統計的予測 (上)(下) (原題: Pattern Recognition and Machine Learning), シュプリンガー・ジャパン, 2007-2008. (鹿島は6章および付録Cの翻訳を担当)
  2. 山名 早人(監訳), 石川 隼輔, 堀井 洋, 村上 明子, 鹿島 久嗣, 小柳 光生(訳), Rael Dornfest, Paul Bausch, Tara Calishain(著): Google Hacks 第3版 プロが使うテクニック & ツール 100選, O'Reilly Japan, 2007.
  3. Jim Spohrer, Paul P. Maglio, Jeffrey T. Kreulen, Savitha Srinivasan(著), 恐神 貴行, 鹿島 久嗣, 加納 真, 水田 秀行(訳): Becoming a Service Scientist, 情報処理, Vol. 47, No. 5, pp. 461-466, 2006.
  4. 山名 早人(監訳), 石川 隼輔, 堀井 洋, 村上 明子, 鹿島 久嗣, 小柳 光生(訳), Tara Calishain, Rael Dornfest(著): Google Hacks 第2版 プロが使うテクニック & ツール 100選, O'Reilly Japan, 2005.

その他の記事/報告/テクニカルレポート

  1. 鹿島 久嗣: The 21st International Conference on Machine Learning (ICML) 2004 参加報告, 人工知能学会誌, Vol. 20, No. 1, 2005.
  2. 瀧本 英二, 鹿島 久嗣, 黒木 学: Banff (COLT, ICML, UAI) 参加報告, 電子情報通信学会 情報・システムソサイエティ誌, Vol. 9, No. 3, 2004.
  3. 鹿島 久嗣: Web探訪 : カーネル法, 人工知能学会誌, Vol. 18, No. 2, pp. 208-209, 2003.

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