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Hisashi Kashima
Professor, Kyoto University, Japan

Hisashi Kashima is a professor at Department of Intelligence Science and Technology, Kyoto University. Before joining the faculty, he was a research staff member of Data Analytics Group in Tokyo Research Laboratory of IBM Research during April, 1999-July, 2009, and was an associate professor at Department of Mathematical Informatics, The University of Tokyo during August, 2009-March, 2014. His research focuses on foundations of machine learning and data mining, and on their advanced applications to various fields, including marketing, bio-/chemo-informatics, and industrial/business intelligence. His previous research work includes development of kernel methods for structured data such as trees and graphs, predictive modeling of networks including biological and social networks, and anomaly detection for industrial systems. He is recently interested in human computation and crowdsourcing, especially on quality control and crowdsourced data analytics. He also contributes to business based on machine learning techniques, and to a number of issued and disclosed patents. He obtained his B.S. degree in applied mathematics and physics in 1997, and an M.S. degree in systems engineering in 1999, and a Ph.D. degree in informatics in 2007 from Kyoto University in Japan.

You can also see his past publications at :

• Google Scholar
• DBLP

Awards

• 2021 Best Paper Award, Japanese Society for Artificial Intelligence
• 2019 JSPS Prize, Japan Society for the Promotion of Science
• 2013 Best Paper Award, Japanese Society for Artificial Intelligence
• 2013 Advisor and co-author of PAKDD 2013 Best Student Paper Runner Up Award winner Yoshifumi Aimoto
• 2013 Funai Award, Funai Foundation for Information Technology
• 2012 MSR Japan New Faculty Award
• 2012 IPSJ Yamashita SIG Research Award, Information Processing Society of Japan
• 2011 Advisor and co-author of ECML PKDD 2011 Best Student Paper Award winners Atsuhiro Narita and Kohei Hayashi
• 2010 IPSJ Best Paper Award, Information Processing Society of Japan
• 2009 IPSJ Nagao Special Researcher Award, Information Processing Society of Japan
• 2008 Incentive Award, Japanese Society for Artificial Intelligence (SIG Data Mining and Statistical Mathematics)
• 2007 Winner, IEEE Data Mining Contest 2007 (winner in Task 1 and second-runner up in Task 2)
• 2007 Best Paper Award, Japanese Society for Artificial Intelligence
• 2004 Incentive Award, Japanese Society for Artificial Intelligence (SIG Knowledge-based Systems)

Publications

Dissertation

• Hisashi Kashima: Machine Learning Approaches for Structured Data, Graduate School of Informatics, Kyoto University, 2007.

Journal Papers

55. Jiuding Duan, Hisashi Kashima. Learning to Rank for Multi-step Ahead Time-Series Forecasting. IEEE Access, 2021.
54. Shogo Hayashi, Yoshinobu Kawahara, Hisashi Kashima. Active Change Point Detection. Journal of Japanese Society of Artificial Intelligence, Vol.35, No.5, 2020. [in Japanese] (JSAI Best Paper Award)
53. Shogo Hayashi, Akira Tanimoto, Hisashi Kashima. Long-Term Prediction of Small Time-Series Data Using Generalized Distillation. Journal of Japanese Society of Artificial Intelligence, Vol.35, No.5, 2020. [in Japanese]
52. Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki, Yukino Baba, Ichigaku Takigawa, Yoshihiro Yamanishi, Hisashi Kashima. Dual Graph Convolutional Neural Network for Predicting Chemical Networks. BMC Bioinformatics (presented at GIW/ABACBS 2019), 2020.
51. Eli Kaminuma, Yukino Baba, Masahiro Mochizuki, Hirotaka Matsumoto, Haruka Ozaki, Toshitsugu Okayama, Takuya Kato, Shinya Oki, Takatomo Fujisawa, Yasukazu Nakamura, Masanori Arita, Osamu Ogasawara, Hisashi Kashima Toshihisa Takagi. DDBJ Data Analysis Challenge: A Machine Learning Competition to Predict Arabidopsis Chromatin Feature Annotations from DNA Sequences. Genes & Genetic Systems, Vol. 95, 2020.
50. Shun Ito, Yukino Baba, Tetsu Isomura, Hisashi Kashima. Synthetic Accessibility Assessment Using Auxiliary Responses. Expert Systems with Applications (ESWA), 2020.
49. Jiyi Li, Yukino Baba, Hisashi Kashima. Hyper Questions: Crowdsourcing Answer Aggregation Method for Questions Requiring Expert Knowledge. DBSJ Japanese Journal, Vol.17-J, 2019. [in Japanese]
48. Yukino Baba, Tetsu Isomura, Hisashi Kashima. Wisdom of Crowds for Synthetic Accessibility Evaluation. Journal of Molecular Graphics and Modelling, Vol.80, pp.217-223, 2018.
47. Atsuto Seko, Hiroyuki Hayashi, Hisashi Kashima, Isao Tanaka. Matrix- and Tensor-based Recommender Systems for the Discovery of Currently Unknown Inorganic Compounds. Physical Review Materials, Vol.2, No.1, 2018.
46. Takuya Kuwahara, Yukino Baba, Hisashi Kashima, Takeshi Kishikawa, Junichi Tsurumi, Tomoyuki Haga, Yoshihiro Ujiie, Takamitsu Sasaki, Hideki Matsushima. Supervised and Unsupervised Intrusion Detection Based on CAN Message Frequencies for In-Vehicle Network. Journal of Information Processing, Vol.26, pp.306-313 2018.
45. 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.
44. Nozomi Nori, Hisashi Kashima, Kazuto Yamashita, Hiroshi Ikai, Yuichi Imanaka. Multi-Task Learning for Disease-Specific Risk Modeling of ICU Patients. IEICE Transactions, Vol.J100-D, No.2, pp.194-204, 2017. [in Japanese]
43. 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.
42. Yukino Baba, Kei Kinoshita, Hisashi Kashima. Participation Recommendation System for Crowdsourcing Contests. Expert Systems With Applications, Vol.43, pp.174-183, 2016.
41. 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..
40. Shunsuke Kajimura, Yukino Baba, Hiroshi Kajino, Hisashi Kashima. Quality Control for Crowdsourced Enumeration. Journal of Japanese Society of Artificial Intelligence, Vol.31, No.2, p.K-F79_1-9, 2016. [in Japanese]
39. 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.
38. Nozomi Nori, Danushka Bollegara, Hisashi Kashima. Simultaneous Higher-order Relation Prediction via Collective Incidence Matrix Embedding. Journal of Japanese Society of Artificial Intelligence, Vol.30, No.2, pp.459-465, 2015. [in Japanese]
37. 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.
36. Hiroshi Kajino, Hiromi Arai, and Hisashi Kashima. Preserving Worker Privacy in Crowdsourcing. Data Mining and Knowledge Discovery, Vol.27, No.5-6, pp.1314-1335, 2014.
35. Yukino Baba, Hisashi Kashima, Kei Kinoshita, Goushi Yamaguchi and 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.
34. Nozomi Nori, Danushka Bollegara, Hisashi Kashima: A Dimension Reduction Approach to Multinomial Relation Prediction, Journal of Japanese Society of Artificial Intelligence, Vol.29, No.1, pp.168-176, 2014. [in Japanese]
33. Hiroto Saigo, Hisashi Kashima and 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.
32. Hiroshi Kajino, Yuta Tsuboi, Issei Sato and Hisashi Kashima: Learning from Crowds and Experts, Journal of Japanese Society of Artificial Intelligence, Vol.28, No.3, pp.XXX-XXX, 2013. [in Japanese]
31. Xu Sun, Hisashi Kashima and Naonori Ueda: Large-Scale Personalized Human Activity Recognition Using Online Multi-Task Learning, Transactions on Knowledge and Data Engineering, Vol.XX, No.X, pp.XXX-XXX, 2012.
30. Satoshi Oyama, Kohei Hayashi and 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.
29. Atsuhiro Narita, Kohei Hayashi, Ryota Tomioka and Hisashi Kashima: Tensor Factorization Using Auxiliary Information, Data Mining and Knowledge Discovery, Vol.25, No.2, pp.298-324, 2012.
28. Kohei Hayashi, Takeshi Takenouchi, Ryota Tomioka and Hisashi Kashima: Self-measuring Similarity for Multi-task Gaussian Process, Journal of Japanese Society of Artificial Intelligence, Vol.27, No.3, pp.103-110, 2012. [in Japanese]
27. Hiroshi Kajino and Hisashi Kashima: Convex Formulations of Multi-task Learning from Crowds, Journal of Japanese Society of Artificial Intelligence, Vol.27, No.3, pp.133-142, 2012. [in Japanese]
26. Junichiro Mori, Yuya Kajikawa, Hisashi Kashima and 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.
25. Daisuke Kimura, Tetsuji Kuboyama, Tetsuo Shibuya and Hisashi Kashima: A Subpath Kernel for Rooted Unordered Trees, Journal of Japanese Society of Artificial Intelligence, Vol.26, No.3, pp.473-482, 2011. [in Japanese]
24. Reiji Teramoto and 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.
23. Yosuke Ozawa, Rintaro Saito, Shigeo Fujimori, Hisashi Kashima, Masamichi Ishizaka, Hiroshi Yanagawa, Etsuko Miyamoto-Sato and Masaru Tomita: Protein Complex Prediction via Verifying and Reconstructing the Topology of Domain-domain Interactions, BMC Bioinformatics, Vol. 11, No. 350, 2010.
22. Hisashi Kashima, Satoshi Oyama, Yoshihiro Yamanishi and 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.
21. Masashi Sugiyama, Hirotaka Hachiya, Hisashi Kashima and 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.
20. Hirofumi Matsuzawa, Shohei Hido, Tsuyoshi Ide and Hisashi Kashima: Unsupervised Change Analysis Using Supervised Learning, IEICE Transaction on Information and Systems, Vol. J93-D, No. 6, pp. 816-825, 2010. [in Japanese]
19. Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi Sugiyama and Takafumi Kanamori: Statistical Outlier Detection Using Direct Density Ratio Estimation, Knowledge and Information Systems, 2010. (to appear)
18. Shohei Hido, Hisashi Kashima and Yutaka Takahashi: Roughly-balanced Bagging for Imbalanced Data, Statistical Analysis and Data Mining, 2010. (to appear)
17. Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama and Kiyoshi Asai: Conic Programming for Multi-task Learning, IEEE Transactions on Knowledge and Data Engineering, Vol.12, No.7, pp.957-968, 2010.
16. Hisashi Kashima and 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.
15. Hiroto Saigo, Masahiro Hattori, Hisashi Kashima and 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.
14. Hisashi Kashima, Yoshihiro Yamanishi, Tsuyoshi Kato, Masashi Sugiyama and 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.
13. Yuta Tsuboi, Shinsuke Mori, Hisashi Kashima, Hiroki Oda and Yuji Matsumoto: Training Conditional Random Fields Using Partial Annotations for Domain Adaptation of Japanese Word Segmentation, IPSJ Journal, Vol. 50, No. 6, pp. 1234-1247, 2009. [in Japanese] (IPSJ Best Paper Award)
12. Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen Bickel and Masashi Sugiyama: Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation, Journal of Information Processing, Vol. 17, pp.138-155, 2009.
11. Tsuyoshi Kato, Hisashi Kashima and Masashi Sugiyama: Robust Label Propagation on Multiple Networks, IEEE Transactions on Neural Networks, Vol.20, No.1, pp. 35-44, 2009.
10. Masashi Sugiyama, Taiji Suzuki, Shinichi Nakajima, Hisashi Kashima, Paul von Bunau and Motoaki Kawanabe: Direct Importance Estimation for Covariate Shift Adaptation, Annals of the Institute of Statistical Mathematics, Vol.60, No.4, 2008.
9. Hisashi Kashima, Shoko Suzuki, Shohei Hido, Yuta Tsuboi, Toshihiro Takahashi, Tsuyoshi Ide, Rikiya Takahashi and 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.
8. Shoko Suzuki, Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Toshihiro Takahashi, Tsuyoshi Ide, Rikiya Takahashi and 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.
7. 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.
6. Tetsuji Kuboyama, Hisashi Kashima, Kiyoko F. Aoki-Kinoshita, Kouichi Hirata and Hiroshi Yasuda: A Spectrum Tree Kernel, Journal of Japanese Society of Artificial Intelligence, Vol.22, No.2, 2007.
5. Hisashi Kashima, Naoki Abe: A Parameterized Probabilistic Model of Network Evolution for Supervised Link Prediction, Journal of Japanese Society of Artificial Intelligence, Vol. 22, No. 2, 2007. [in Japanese]
4. Hisashi Kashima, Tadashi Tsumura, Tsuyoshi Ide, Takahide Nogayama, Ryo Hirade, Hiroaki Etoh and Takeshi Fukuda: Network-Based Problem Detection for Distributed Systems, IEICE Transaction, Vol. J89-D, No. 2, 2006. [in Japanese]
3. Hisashi Kashima, Hiroshi Sakamoto and Teruo Koyanagi: Design and Analysis of Convolution Kernels for Tree-Structured Data, Journal of Japanese Society of Artificial Intelligence, Vol. 21, No. 1, 2006. [in Japanese] (JSAI Best Paper Award)
2. Tetsuo Shibuya, Hisashi Kashima and Akihiko Konagaya: Efficient Filtering Methods for Clustering cDNAs with Spliced Sequence Alignment, Bioinformatics, 2003.
1. Takanori Fukao, Hisashi Kashima and Norihiko Adachi: Decentralized Adaptive Control with Improved Transient Performance, Transactions of the Society of Instrument and Control Engineers, Vol.35, No.7, pp. 869-878, 1999

Books/Chapters/Review Articles

9. 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.
8. Tetsuo Shibuya, Hisashi Kashima, Jun Sese and Shandar Ahmad (Eds.): Pattern Recognition in Bioinformatics, Proceedings of the 7th IAPR International Conference (PRIB 2012), Lecture Notes in Computer Science, Vol.7632, 2012.
7. Hisashi Kashima: Graph Mining, Journal of IEICE, Vol.93, No.9, pp.797-802, 2010. [in Japanese]
6. 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.
5. 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.
4. 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, 2009.
3. Hisashi Kashima: Kernel Methods for Analyzing Structured Data, Technical Report of IEICE "Pattern Recognition and Media Understanding", 2005. [in Japanese]
2. Hisashi Kashima: Kernel Methods for Mining Structured Data, IPSJ Magazine, 2005. [in Japanese]
1. Hisashi Kashima, Koji Tsuda and Akihiro Inokuchi: Kernels for Graphs, Kernel Methods in Computational Biology, MIT Press, 2004.

Patents (granted in U.S.)

13. Shohei Hido, Hisashi Kashima (IBM): Graph Similarity Calculation System, Method and Program, U.S.Patent:9122771&8588531.
12. Shohei Hido, Ysuyoshi Ide, Hisashi Kashima, Harunobu Kubo, Hirofumi Matsuzawa (IBM): Change Analysis, U.S.Patent:8417648.
11. Shohei Hido, Tsuyoshi Ide, Hisashi Kashima, Shoko Suzuki, Akira Tajima, Rikiya Takahashi, Toshihiro Takahashi, Yuta Tsuboi (IBM): Location estimation system, method and program, U.S.Patent:8138974.
10. Hisashi Kashima, Kazutaka Yamasaki (IBM): Method for Regression from Interval Target Values by Alternating Linear Gaussian and Expectation-Maximization, U.S.Patent:8140447.
9. 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.
8. Hisashi Kashima (IBM): Method and System for L1-based Robust Distribution Clustering of Multinomial Distributions, U.S.Patent:7996340.
7. Hiroaki Etoh, Ryo Hirade, Hisashi Kashima, Tsuyoshi Ide (IBM): Computer Operation Analysis, U.S.Patent:7493361.
6. Hisashi Kashima (IBM): System for Supporting User's Behavior, U.S.Patent: 7467120.
5. Tsuyoshi Ide, Kunikazu Yoda, Hisashi Kashima (IBM), Hiroaki Etoh, Ryo Hirade: Anomaly Detection, U.S.Patent: 7346803.
4. Akihiro Inokuchi, Hisashi Kashima (IBM): Classification Factor Detection, U.S.Patent: 7337186.
3. Hisashi Kashima, Yasumasa Kajinaga (IBM): Auction Method and Auction System, and StorageMmedium Therefor, U.S.Patent: 7231365.
2. Hisashi Kashima, Teruo Koyanagi (IBM): Classification Method of Labeled Ordered Trees Using Support Vector Machines, U.S.Patent: 7130,833.
1. Tetsuo Shibuya, Hisashi Kashima (IBM): Database Search Device, Database Search System, Database Search Method, Program and Storage Medium, U.S.Patent: 6928437.

(For patents granted in Japan please refer to my Japanese page.)

Conference Papers (refereed)

131. Shonosuke Harada, Hisashi Kashima. GraphITE: Estimating Individual Effects of Graph-structured Treatments. In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM), 2021.
130. Takako Onishi, Hisashi Kashima. Machine Failure Diagnosis by Combining Software Log and Sensor Data. In Proceedings of IEEE International Conference on Electrical, Control and Instrumentation Engineering (ICECIE), 2021.
129. Lu Xiaotian, Arseny Tolmachev, Tatsuya Yamamoto, Koh Takeuchi, Seiji Okajima, Tomoyoshi Takebayashi, Koji Maruhashi, Hisashi Kashima. Crowdsourcing Evaluation of Saliency-based XAI Methods. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2021.
128. Luu Huu Phuc, Koh Takeuchi, Seiji Okajima, Arseny Tolmachev, Tomoyoshi Takebayashi, Koji Maruhashi, Hisashi Kashima. Inter-domain Multi-relational Link Prediction. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2021.
127. Shu Nakamura, Koh Takeuchi, Hisashi Kashima, Takeshi Kishikawa, Takashi Ushio, Tomoyuki Haga, Takamitsu Sasaki. In-Vehicle Network Attack Detection Across Vehicle Models: A Supervised-Unsupervised Hybrid Approach. In Proceedings of the 24th IEEE International Intelligent Transportation Systems Conference (ITSC), 2021.
126. Maya Okawa, Tomoharu Iwata, Yusuke Tanaka, Hiroyuki Toda, Takeshi Kurashima, Hisashi Kashima. Dynamic Hawkes Processes for Discovering Time-evolving Communities’ States behind Diffusion Processes. In Proceedings of the 27st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021.
125. Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima. Causal Combinatorial Factorization Machines for Set-wise Recommendation. In Proceedings of the 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2021.
124. Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima. Regret Minimization for Causal Inference on Large Treatment Space. In Proceedings of The 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 2021.
123. Yoichi Chikahara, Shinsaku Sakaue, Akinori Fujino, Hisashi Kashima. Learning Individually Fair Classifier with Path-Specific Causal-Effect Constraint. In Proceedings of The 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 2021.
122. Ryoma Sato, Makoto Yamada, Hisashi Kashima. Random Features Strengthen Graph Neural Networks. In Proceedings of SIAM International Conference on Data Mining (SDM), 2021.
121. Koh Takeuchi, Ryo Nishida, Hisashi Kashima, Masaki Onishi. Grab the Reins of Crowds: Estimating the Effects of Crowd Movement Guidance Using Causal Inference. In Proceedings of 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2021.
120. Ryoma Sato, Makoto Yamada, Hisashi Kashima. Fast Unbalanced Optimal Transport on Tree. In Advances in Neural Information Processing Systems (NeurIPS 2020), 2020.
119. Luu Huu Phuc, Koh Takeuchi, Makoto Yamada, Hisashi Kashima. Simultaneous Link Prediction on Unaligned Networks Using Graph Embedding and Optimal Transport. In Proceedings of the the 7th IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2020.
118. Hitoshi Kusano, Yuji Horiguchi, Yukino Baba, Hisashi Kashima. Stress Prediction from Head Motion. In Proceedings of the the 7th IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2020.
117. Yukino Baba, Jiyi Li, Hisashi Kashima. CrowDEA: Multi-view Idea Prioritization with Crowds. In Proceedings of the 8th AAAI Conference on Human Computation and Crowdsourcing (HCOMP),, 2020.
116. Yan Gu, Jiuding Duan, Hisashi Kashima. An Intransitivity Model for Matchup and Pairwise Comparison. In Proceedings of the 25th International Conference on Pattern Recognition (ICPR), 2020.
115. Shounosuke Harada, Hisashi Kashima. Counterfactual Propagation for Semi-Supervised Individual Treatment Effect Estimation. In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2020.
114. Yasutoshi Ida, Sekitoshi Kanai,Yasuhiro Fujiwara, Tomoharu Iwata, Koh Takeuchi, Hisashi Kashima. Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance. In Proceedings of the 37th International Conference on Machine Learning (ICML), 2020.
113. Jiyi Li, Yasushi Kawase, Yukino Baba, Hisashi Kashima. Performance as a Constraint: An Improved Wisdom of Crowds Using Performance Regularization. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI), 2020.
112. Tatsuya Shiraishi, Tam Le, Hisashi Kashima, Makoto Yamada Topological Bayesian Optimization with Persistence Diagrams. In Proceedings of the 24th European Conference on Artificial Intelligence (ECAI), 2020.
111. Ryoma Sato, Makoto Yamada, Hisashi Kashima. Approximation Ratios of Graph Neural Networks for Combinatorial Problems. In Advances in Neural Information Processing Systems (NeurIPS), 2019.
110. Yasutoshi Ida, Yasuhiro Fujiwara, Hisashi Kashima. Fast Sparse Group Lasso. In Advances in Neural Information Processing Systems (NeurIPS), 2019.
109. Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric Gouy-Pailler, Jamal Atif. Theoretical Evidence for Adversarial Robustness Through Randomization. In Advances in Neural Information Processing Systems (NeurIPS), 2019.
108. Shogo Hayashi, Yoshinobu Kawahara, Hisashi Kashima. Active Change-Point Detection. In Proceedings of the 11th Asian Conference on Machine Learning (ACML), 2019.
107. Ryoma Sato, Makoto Yamada, Hisashi Kashima. Learning to Sample Hard Instances for Graph Algorithms. In Proceedings of the 11th Asian Conference on Machine Learning (ACML), 2019.
106. Shonosuke Harada, Kazuki Taniguchi, Makoto Yamada, Hisashi Kashima. Context-Regularized Neural Collaborative Filtering for Game App Recommendation In ACM RecSys LBR track, 2019.
105. Daiki Tanaka, Makoto Yamada, Hisashi Kashima, Takeshi Kishikawa, Tomoyuki Haga, Takamitsu Sasaki. In-Vehicle Network Intrusion Detection and Explanation Using Density Ratio Estimation. In Proceedings of 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2019.
104. Daiki Tanaka, Yukino Baba, Hisashi Kashima, Yuta Okubo. Large-scale Driver Identification Using Automobile Driving Data. In Proceedings of 2019 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2019.
103. Shonosuke Harada, Kazuki Taniguchi, Makoto Yamada, Hisashi Kashima. In-app Purchase Prediction Using Bayesian Personalized Dwell Day Ranking. In Proceedings of AdKDD 2019 Workshop (AdKDD), 2019.
102. Kosuke Yoshimura, Tomoaki Iwase, Yukino Baba, Hisashi Kashima. Interdependence Model for Multi-label Classification. In Proceedings of the 28th International Conference on Artificial Neural Networks (ICANN), 2019.
101. Takeru Sunahase, Yukino Baba, Hisashi Kashima. Probabilistic Modeling of Peer Correction and Peer Assessment. In Proceedings of the 12th International Conference on Educational Data Mining (EDM), 2019.
100. Shogo Hayashi, Akira Tanimoto, Hisashi Kashima. Long-Term Prediction of Small Time-Series Data Using Generalized Distillation. In Proceedings of the 2019 International Joint Conference on Neural Networks (IJCNN), 2019.
99. Yusuke Sakata, Yukino Baba, Hisashi Kashima. CrowNN: Human-in-the-loop Network with Crowd Crowd-generated Inputs. In Proceedings of the 44th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019.
98. Jill-J?nn Vie, Hisashi Kashima. Factorization Machines for Knowledge Tracing. In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI), 2019.
97. Hirotaka Akita, Kosuke Nakago, Tomoki Komatsu, Yohei Sugawara, Shin-ichi Maeda, Yukino Baba, Hisashi Kashima. BayesGrad: Explaining Predictions of Graph Convolutional Networks. In Proceedings of the 25th International Conference on Neural Information Processing (ICONIP), 2018.
96. Ryoma Sato, Takehiro Yamamoto, Hisashi Kashima. Short-term Precipitation Prediction with Skip-connected PredNet. In Proceedings of the 27th International Conference on Artificial Neural Networks (ICANN), 2018.
95. Jiyi Li, Hisashi Kashima. Incorporating Worker Similarity for Label Aggregation in Crowdsourcing. In Proceedings of the 27th International Conference on Artificial Neural Networks (ICANN), 2018.
94. Jiyi Li, Yukino Baba, Hisashi Kashima. Simultaneous Clustering and Ranking from Pairwise Comparisons. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), pp.XX-XX, 2018.
93. Guoxi Zhang, Tomoharu Iwata, Hisashi Kashima. On Reducing Dimensionality of Labeled Data Efficiently. In Proceedings of the 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2018.
92. Takuya Kuwahara, Yukino Baba, Hisashi Kashima, Takeshi Kishikawa, Junichi Tsurumi, Tomoyuki Haga, Yoshihiro Ujiie, Takamitsu Sasaki, Hideki Matsushima. Payload-based Statistical Intrusion Detection for In-vehicle Networks. In Proceedings of the Australian Workshop on Machine Learning for Cyber-security (co-located with PAKDD 2018), 2018
91. Ryusuke Takahama, Yukino Baba, Nobuyuki Shimizu, Sumio Fujita, Hisashi Kashima. AdaFlock: Adaptive Feature Discovery for Human-in-the-loop Predictive Modeling. In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI), 2018.
90. Yukino Baba, Tomoumi Takase, Kyohei Atarashi, Satoshi Oyama, Hisashi Kashima. Data Analysis Competition Platform for Educational Purposes: Lessons Learned and Future Challenges. In Proceedings of the 8th Symposium on Educational Advances in Artificial Intelligence (EAAI), 2018.
89. Junpei Naito, Yukino Baba, Hisashi Kashima, Takenori Takaki, Takuya Funo. Predictive Modeling of Learning Continuation in Preschool Education Using Temporal Patterns of Development Tests In Proceedings of the 8th Symposium on Educational Advances in Artificial Intelligence (EAAI), 2018.
88. Koh Takeuchi, Hisashi Kashima, Naonori Ueda. Autoregressive Tensor Factorization for Spatio-temporal Predictions. In Proceedings of the 2017 IEEE International Conference on Data Mining (ICDM), 2017.
87. 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.
86. 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.
85. 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.
84. 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.
83. 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.
82. 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.
81. 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.
80. 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.
79. 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.
78. Kaito Fujii, Hisashi Kashima. Budgeted Stream-based Active Learning via Adaptive Submodular Maximization. In Advances in Neural Information Processing Systems (NIPS) 29, 2016.
77. 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.
76. 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.
75. 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.
74. 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.
73. 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.
72. 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.
71. 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.
70. 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.
69. 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.
68. 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.
67. 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.
66. 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.
65. 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.
64. Hiroshi Kajino, Yukino Baba, Hisashi Kashima. Instance-privacy Preserving Crowdsourcing. In Proc. 2nd Conference on Human Computation and Crowdsourcing (HCOMP), Pittsburgh, USA, 2014.
63. 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.
62. Toshiko Matsui, Yukino Baba, Toshihiro Kamishima, Hisashi Kashima. Crowdordering. In Proc. 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp.336-347, Tainan, Taiwan, 2014.
61. Jingjing Wang, Satoshi Oyama, Masahito Kurihara, 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.
60. Yukino Baba, 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.
59. 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.
58. 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.
57. 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.
56. 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)
55. 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.
54. 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.
53. 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.
52. 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.
51. 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.
50. 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.
49. 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.
48. 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.
47. 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.
46. 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)
45. 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.
43. 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.
42. 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.
41. 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.
40. 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.
39. 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.
38. 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.
37. 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.
36. 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.
35. 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.
34. 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.
33. 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 (APBC), Bangalore, India, 2010.
32. Shohei Hido and Hisashi Kashima: A Linear-time Graph Kernel, In Proc. 9th IEEE International Conference on Data Mining (ICDM), Miami, Florida, USA, 2009.
31. Mutsumi Fukuzaki, Mio Seki, Hisashi Kashima and Jun Sese: Side Effect Prediction Using Cooperative Pathways. In Proc. IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM), Washington D.C., USA, 2009.
32. 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), Kobe, Japan, 2009.
31. 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), Bangkok, Thailand, 2009.
30. 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, USA, 2009.
29. 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), Pisa, Italy, 2008.
28. Hisashi Kashima, Jianying Hu, Bonnie Ray and Moninder Singh: K-means Clustering of Proportional Data Using L1 Distance, In Proc. 19th International Conference on Pattern Recognition (ICPR), Tampa, Florida, USA, 2008.
27. 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.
26. Hisashi Kashima, Kazutaka Yamasaki, Hiroto Saigo and Akihiro Inokuchi: Regression with Interval Output Values, In Proc. 19th International Conference on Pattern Recognition (ICPR), Tampa, Florida, USA, 2008.
25. Yuta Tsuboi, Hisashi Kashima, Shinsuke Mori, Hiroki Oda and Yuji Matsumoto: Training Conditional Random Fields Using Incomplete Annotations (presentation slides), In Proc. 22nd International Conference on Computational Linguistics (COLING), Manchester, UK, 2008.
24. 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), Osaka, Japan, 2008.
23. 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), Atlanta, Georgia, USA, 2008.
22. Shohei Hido and Hisashi Kashima: Roughly Balanced Bagging for Imbalanced Data, In Proc. 2008 SIAM International Conference on Data Mining (SDM), Atlanta, Georgia, USA, 2008.
21. Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen Bickel and Masashi Sugiyama: Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation （presentation slides）, In Proc. 2008 SIAM International Conference on Data Mining (SDM), Atlanta, Georgia, USA, 2008.
20. 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 (presentation slides), In IEEE ICDM Data Mining Contest, Omaha, Nebraska, USA, 2007 (winner for Task 1 out of 15 teams)
19. 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 (second runner up for Task 2 out of 17 teams)
18. 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 (NIPS2007), Vancouver, B.C., Canada, 2007.
17. 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 (NIPS2007), Vancouver, B.C., Canada, 2007.
16. 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.
15. 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 (GIW2006), Yokohama, Japan, 2006.
14. 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 (ICDM2006), Hong Kong, 2006.
13. 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 (DMSS2006), Sapporo, Japan, 2006.
12. 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.
11. Hisashi Kashima: Risk-Sensitive Learning via Expected Shortfall Minimization (Extended Abstract), In Proc. 2006 SIAM Conference on Data Mining (SDM06), Bethesda, Maryland, USA, 2006. (full paper version)
10. 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 (ICDE2005), Tokyo, Japan, 2005.
9. Tsuyoshi Ide and Hisashi Kashima: Eigenspace-based Anomaly Detection in Computer Systems, In Proc. 10th ACM SIGKDD Conference (KDD2004), Seattle, Washington, USA, 2004.
8. Hisashi Kashima and Yuta Tsuboi: Kernel-Based Discriminative Learning Algorithms for Labeling Sequences, Trees and Graphs, In Proc. 21st International Conference on Machine Learning (ICML2004), Banff, Alberta, Canada, 2004.
7. 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 (GIW2003), Yokohama, Japan, 2003.
6. 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 (ICDM2003), Melbourne, Florida, USA, 2003.
5. Hisashi Kashima , Koji Tsuda and Akihiro Inokuchi: Marginalized Kernels Between Labeled Graphs, In Proc. 20th International Conference on Machine Learning (ICML2003), Washington DC, USA, 2003.
4. Hisashi Kashima and Akihiro Inokuchi: Kernels for Graph Classification, In Proc. 1st ICDM Workshop on Active Mining (AM-2002), Maebashi, Japan, 2002.
3. Hisashi Kashima and Teruo Koyanagi: Kernels for Semi-Structured Data, In Proc. 19th International Conference on Machine Learning (ICML2002), Sydney, Australia, 2002.
2. 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.
1. 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.

Conference Papers (unrefereed)

14. Yuta Tsuboi, Hisashi Kashima, Shinsuke Mori, Hiroki Oda and Yuji Matsumoto: Training Conditional Random Fields using Partial and Ambiguous Structured Labels, In Technical Report of IPSJ SIG-NLP (NL-182), 2007. [in Japanese]
13. Hisashi Kashima, Kazutaka Yamasaki, Hiroto Saigo and Akihiro Inokuchi: Regression with Intervals, The International Workshop on Data-Mining and Statistical Science (DMSS2007), 2007. [in Japanese] (JSAI Incentive Award)
12. Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashima, Paul von Bunau and Motoaki Kawanabe: Kullback-Leibler importance estimation procedure for covariate shift adaptation, The International Workshop on Data-Mining and Statistical Science (DMSS2007), 2007.
11. Tetsuji Kuboyama, Koichi Hirata and Hisashi Kashima and Kiyoko F. Aoki-Kinoshita: The Gram Distribution Kernel: A Tree Kernel for Glycan Classification, In Technical Report of Japanese Society of Artificial Intelligence, SIG-FPAI, 2006.
10. Hisashi Kashima: Risk-Sensitive Classification Learning, In Proc. 8th Information-Based Induction Sciences (IBIS 2005), 2005. [in Japanese]
9. Yuta Tsuboi and Hisashi Kashima: Design of Discriminative Models for Labeling Structured Data, In Proc. 8th Information-Based Induction Sciences (IBIS 2005), 2005. [in Japanese]
8. Tsuyoshi Ide and Hisashi Kashima: Eigenspace Approach to Anomaly Detection of Computer Systems, In Proc. Annual Conference of Japanese Society of Artificial Intelligence, 2004. [in Japanese]
7. Hisashi Kashima and Yuta Tsuboi: Kernel-based Discriminative Learning Algorithms for Labeling Sequences, Trees and Graphs, In Technical Report of The Institute for Electronics, Information and Communication Engineers, AI, 2004. [in Japanese]
6. Akihiro Inokuchi and Hisashi Kashima: Discovering Significant Pairs of Patterns from Graph Structures with Class Labels, In Technical Report of Japanese Society of Artificial Intelligence, SIG-KBS, 2004. [in Japanese] (JSAI Incentive Award)
5. Tetsuo Shibuya, Chris Schoenbach, Hisashi Kashima and Akihiko Konagaya: Accurate cDNA Clustering Algorithm based on Spliced Sequence Alignment, In Technical Report of The Institute for Electronics, Information and Communication Engineers, COMP-2002-9-14, 17-24, 2002.
4. Hisashi Kashima and Teruo Koyanagi: Kernels for Semi-Structured Data, In Technical Report of Japanese Society of Artificial Intelligence, SIG-FAI-A104, 2002. [in Japanese]
3. Hisashi Kashima: Inferring Genetic Networks from Gene Expression Data Using Probabilistic Boolean Network Models, In Technical Report of Japanese Society of Artificial Intelligence, SIG-MBI, 2001. [in Japanese]
2. Hisashi Kashima: Attribute Selection Using Multplicative Update, In Proc. Annual Conference of Japanese Society of Artificial Intelligence, 2001. [in Japanese]
1. Hisashi Kashima and Yasumasa Kajinaga: Optimal Winner Determination Algorithms for E-procurement Auction, In Techinical Report of The Institute for Electronics, Information and Communication Engineers, COMP-2000-57-63, 17-23, 2000.

Technical Reports

6. Yuta Tsuboi and Hisashi Kashima, A New Loss Function with ``Markov Property" for Information Extraction, IBM Research Report, RT0660, 2006.
5. Hisashi Kashima, Koji Tsuda and Akihiro Inokuchi: Marginalized Kernels Between Labeled Graphs, IBM Research Report, 2003.
4. Hisashi Kashima and Teruo Koyanagi: Kernels for Semi-structured Data, IBM Research Report, 2003.
3. Hisashi Kashima: On-line Kernel Principal Component Analysis, IBM Research Report, 2002.
2. Hisashi Kashima: Inferring Genetic Networks from Gene Expression Data Using Probabilistic Boolean Network Models, IBM Research Report, 2002.
1. Hisashi Kashima and Yasumasa Kajinaga: Optimal Winner Determination Algorithms for E-procurement Auction, IBM Research Report, 2000.