Hisashi Kashima

Yoshifumi Aimoto, Hisashi Kashima: Matrix Factorization With Aggregated Observations. PAKDD (2) 2013: 521-532

Atsuhiro Narita, Kohei Hayashi, Ryota Tomioka, Hisashi Kashima: Tensor factorization using auxiliary information. Data Min. Knowl. Discov. 25(2): 298-324 (2012)

Junichiro Mori, Yuya Kajikawa, Hisashi Kashima, Ichiro Sakata: Machine learning approach for finding business partners and building reciprocal relationships. Expert Syst. Appl. 39(12): 10402-10407 (2012)

Satoshi Oyama, Kohei Hayashi, Hisashi Kashima: Link Prediction Across Time via Cross-Temporal Locality Preserving Projections. IEICE Transactions 95-D(11): 2664-2673 (2012)

Kohei Hayashi, Takashi Takenouchi, Ryota Tomioka, Hisashi Kashima: Self-measuring Similarity for Multi-task Gaussian Process. Journal of Machine Learning Research - Proceedings Track 27: 145-154 (2012)

Hiroshi Kajino, Yuta Tsuboi, Hisashi Kashima: A Convex Formulation for Learning from Crowds. AAAI 2012

Nozomi Nori, Danushka Bollegala, Hisashi Kashima: Multinomial Relation Prediction in Social Data: A Dimension Reduction Approach. AAAI 2012

Michael E. Houle, Hisashi Kashima, Michael Nett: Generalized Expansion Dimension. ICDM Workshops 2012: 587-594

Daisuke Kimura, Hisashi Kashima: Fast Computation of Subpath Kernel for Trees. ICML 2012

Shohei Hido, Hisashi Kashima: Hash-based structural similarity for semi-supervised Learning on attribute graphs. ICPR 2012: 3009-3012

Michael E. Houle, Hisashi Kashima, Michael Nett: Fast Similarity Computation in Factorized Tensors. SISAP 2012: 226-239

Tetsuo Shibuya, Hisashi Kashima, Jun Sese, Shandar Ahmad (Eds.): Pattern Recognition in Bioinformatics - 7th IAPR International Conference, PRIB 2012, Tokyo, Japan, November 8-10, 2012. Proceedings. Lecture Notes in Computer Science 7632, Springer 2012, isbn 978-3-642-34122-9

Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya, Toshiyuki Tanaka: Parametric Return Density Estimation for Reinforcement Learning. CoRR abs/1203.3497 (2012)

Daisuke Kimura, Hisashi Kashima: Fast Computation of Subpath Kernel for Trees. CoRR abs/1206.4642 (2012)

Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi Sugiyama, Takafumi Kanamori: Statistical outlier detection using direct density ratio estimation. Knowl. Inf. Syst. 26(2): 309-336 (2011)

Yuta Tsuboi, Yuya Unno, Hisashi Kashima, Naoaki Okazaki: Fast Newton-CG Method for Batch Learning of Conditional Random Fields. AAAI 2011

Satoshi Oyama, Kohei Hayashi, Hisashi Kashima: Cross-Temporal Link Prediction. ICDM 2011: 1188-1193

Xu Sun, Hisashi Kashima, Ryota Tomioka, Naonori Ueda, Ping Li: A New Multi-task Learning Method for Personalized Activity Recognition. ICDM 2011: 1218-1223

Ryota Tomioka, Taiji Suzuki, Kohei Hayashi, Hisashi Kashima: Statistical Performance of Convex Tensor Decomposition. NIPS 2011: 972-980

Daisuke Kimura, Tetsuji Kuboyama, Tetsuo Shibuya, Hisashi Kashima: A Subpath Kernel for Rooted Unordered Trees. PAKDD (1) 2011: 62-74

Xu Sun, Hisashi Kashima, Ryota Tomioka, Naonori Ueda: Large Scale Real-Life Action Recognition Using Conditional Random Fields with Stochastic Training. PAKDD (2) 2011: 222-233

Atsuhiro Narita, Kohei Hayashi, Ryota Tomioka, Hisashi Kashima: Tensor Factorization Using Auxiliary Information. ECML/PKDD (2) 2011: 501-516

Hiroto Saigo, Masahiro Hattori, Hisashi Kashima, Koji Tsuda: Reaction graph kernels predict EC numbers of unknown enzymatic reactions in plant secondary metabolism. BMC Bioinformatics 11(S-1): 31 (2010)

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 11: 350 (2010)

Masashi Sugiyama, Hirotaka Hachiya, Hisashi Kashima, Tetsuro Morimura: Least Absolute Policy Iteration--A Robust Approach to Value Function Approximation. IEICE Transactions 93-D(9): 2555-2565 (2010)

Hisashi Kashima, Satoshi Oyama, Yoshihiro Yamanishi, Koji Tsuda: Cartesian Kernel: An Efficient Alternative to the Pairwise Kernel. IEICE Transactions 93-D(10): 2672-2679 (2010)

Tsuyoshi Kato, Kinya Okada, Hisashi Kashima, Masashi Sugiyama: A Transfer Learning Approach and Selective Integration of Multiple Types of Assays for Biological Network Inference. IJKDB 1(1): 66-80 (2010)

Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, Kiyoshi Asai: Conic Programming for Multitask Learning. IEEE Trans. Knowl. Data Eng. 22(7): 957-968 (2010)

Xu Sun, Hisashi Kashima, Takuya Matsuzaki, Naonori Ueda: Averaged Stochastic Gradient Descent with Feedback: An Accurate, Robust, and Fast Training Method. ICDM 2010: 1067-1072

Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya, Toshiyuki Tanaka: Nonparametric Return Distribution Approximation for Reinforcement Learning. ICML 2010: 799-806

Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama, Hisashi Kashima: A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices. ICML 2010: 1087-1094

Mutsumi Fukuzaki, Mio Seki, Hisashi Kashima, Jun Sese: Finding Itemset-Sharing Patterns in a Large Itemset-Associated Graph. PAKDD (2) 2010: 147-159

Rudy Raymond, Hisashi Kashima: Fast and Scalable Algorithms for Semi-supervised Link Prediction on Static and Dynamic Graphs. ECML/PKDD (3) 2010: 131-147

Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya, Toshiyuki Tanaka: Parametric Return Density Estimation for Reinforcement Learning. UAI 2010: 368-375

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 25(22): 2962-2968 (2009)

Hisashi Kashima, Tsuyoshi Idé, Tsuyoshi Kato, Masashi Sugiyama: Recent Advances and Trends in Large-Scale Kernel Methods. IEICE Transactions 92-D(7): 1338-1353 (2009)

Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen Bickel, Masashi Sugiyama: Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation. JIP 17: 138-155 (2009)

Shohei Hido, Hisashi Kashima, Yutaka Takahashi: Roughly balanced bagging for imbalanced data. Statistical Analysis and Data Mining 2(5-6): 412-426 (2009)

Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama: Robust Label Propagation on Multiple Networks. IEEE Transactions on Neural Networks 20(1): 35-44 (2009)

Mutsumi Fukuzaki, Mio Seki, Hisashi Kashima, Jun Sese: Side Effect Prediction Using Cooperative Pathways. BIBM 2009: 142-147

Shohei Hido, Hisashi Kashima: A Linear-Time Graph Kernel. ICDM 2009: 179-188

Masashi Sugiyama, Hirotaka Hachiya, Hisashi Kashima, Tetsuro Morimura: Least absolute policy iteration for robust value function approximation. ICRA 2009: 2904-2909

Hisashi Kashima, Satoshi Oyama, Yoshihiro Yamanishi, Koji Tsuda: On Pairwise Kernels: An Efficient Alternative and Generalization Analysis. PAKDD 2009: 1030-1037

Hisashi Kashima, Tsuyoshi Kato, Yoshihiro Yamanishi, Masashi Sugiyama, Koji Tsuda: Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction. SDM 2009: 1099-1110

Yuta Tsuboi, Hisashi Kashima, Shinsuke Mori, Hiroki Oda, Yuji Matsumoto: Training Conditional Random Fields Using Incomplete Annotations. COLING 2008: 897-904

Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi Sugiyama, Takafumi Kanamori: Inlier-Based Outlier Detection via Direct Density Ratio Estimation. ICDM 2008: 223-232

Hisashi Kashima, Jianying Hu, Bonnie K. Ray, Moninder Singh: K-means clustering of proportional data using L1 distance. ICPR 2008: 1-4

Hisashi Kashima, Kazutaka Yamasaki, Akihiro Inokuchi, Hiroto Saigo: Regression with interval output values. ICPR 2008: 1-4

Yuta Tsuboi, Hisashi Kashima: A new objective function for sequence labeling. ICPR 2008: 1-4

Shohei Hido, Tsuyoshi Idé, Hisashi Kashima, Harunobu Kubo, Hirofumi Matsuzawa: Unsupervised Change Analysis Using Supervised Learning. PAKDD 2008: 148-159

Shohei Hido, Hisashi Kashima: Roughly Balanced Bagging for Imbalanced Data. SDM 2008: 143-152

Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen Bickel, Masashi Sugiyama: Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation. SDM 2008: 443-454

Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama: Integration of Multiple Networks for Robust Label Propagation. SDM 2008: 716-726

Hisashi Kashima: Risk-Sensitive Learning via Minimization of Empirical Conditional Value-at-Risk. IEICE Transactions 90-D(12): 2043-2052 (2007)

Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, Kiyoshi Asai: Multi-Task Learning via Conic Programming. NIPS 2007

Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashima, Paul von Bünau, Motoaki Kawanabe: Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation. NIPS 2007

Hisashi Kashima, Naoki Abe: A Parameterized Probabilistic Model of Network Evolution for Supervised Link Prediction. ICDM 2006: 340-349

Hisashi Kashima: Risk-Sensitive Learning via Expected Shortfall Minimization. SDM 2006

Hisashi Kashima, Tadashi Tsumura, Tsuyoshi Idé, Takahide Nogayama, Ryo Hirade, Hiroaki Etoh, Takeshi Fukuda: Network-Based Problem Detection for Distributed Systems. ICDE 2005: 978-989

Tetsuo Shibuya, Hisashi Kashima, Akihiko Konagaya: Efficient filtering methods for clustering cDNAs with spliced sequence alignment. Bioinformatics 20(1): 29-39 (2004)

Hisashi Kashima, Yuta Tsuboi: Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs. ICML 2004

Tsuyoshi Idé, Hisashi Kashima: Effective Dimension in Anomaly Detection: Its Application to Computer Systems. JSAI Workshops 2004: 189-204

Tsuyoshi Idé, Hisashi Kashima: Eigenspace-based anomaly detection in computer systems. KDD 2004: 440-449

Akihiro Inokuchi, Hisashi Kashima: Mining Significant Pairs of Patterns from Graph Structures with Class Labels. ICDM 2003: 83-90

Hisashi Kashima, Koji Tsuda, Akihiro Inokuchi: Marginalized Kernels Between Labeled Graphs. ICML 2003: 321-328

Hisashi Kashima, Teruo Koyanagi: Kernels for Semi-Structured Data. ICML 2002: 291-298