Hisashi Kashima

288 papers A* 56A 23B 26C 5Misc 3Journal 112Unranked 56

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Adaptive Discovery of Interpretable Audio Attributes with Multimodal LLMs for Low-Resource Classification. CoRR Kosuke Yoshimura, Hisashi Kashima
2026	J	`jnl`	Adaptive Quality-Diversity Trade-offs for Large-Scale Batch Recommendation. CoRR Clémence Réda, Tomas Rigaux, Hiba Bederina, Koh Takeuchi, Hisashi Kashima, Jill-Jênn Vie
2026	J	`jnl`	Evaluating Cross-Modal Reasoning Ability and Problem Characteristics with Multimodal Item Response Theory. CoRR Shunki Uebayashi, Kento Masui, Kyohei Atarashi, Han Bao, Hisashi Kashima, Naoto Inoue, Mayu Otani, Koh Takeuchi
2026	J	`jnl`	Long-Term Outlier Prediction Through Outlier Score Modeling. CoRR Yuma Aoki, Joon Park, Koh Takeuchi, Hisashi Kashima, Shinya Akimoto, Ryuichi Hashimoto, Takahiro Adachi, Takeshi Kishikawa, Takamitsu Sasaki
2026	J	`jnl`	MACC: Multi-Agent Collaborative Competition for Scientific Exploration. CoRR Satoshi Oyama, Yuko Sakurai, Hisashi Kashima
2026	J	`jnl`	Modeling Dynamic Interference for Treatment Effect Estimation from Dynamic Graphs. ACM Trans. Knowl. Discov. Data Xiaofeng Lin, Han Bao, Koh Takeuchi, Yan Cui, Hisashi Kashima
2026	A	`conf`	Robust Post-hoc Score Allocation in Exams. LAK Naoyuki Kita, Jill-Jênn Vie, Koh Takeuchi, Hisashi Kashima
2026	A*	`conf`	Unpacking the Implicit Norm Dynamics of Sharpness-Aware Minimization in Tensorized Models. AAAI Tianxiao Cao, Kyohei Atarashi, Hisashi Kashima
2025	J	`jnl`	Box-Constrained Softmax Function and Its Application for Post-Hoc Calibration. CoRR Kyohei Atarashi, Satoshi Oyama, Hiromi Arai, Hisashi Kashima
2025	Misc	`conf`	Cognitive Biases in Large Language Models: A Survey and Mitigation Experiments. SAC Yasuaki Sumita, Koh Takeuchi, Hisashi Kashima
2025	—	`conf`	Counterfactual Evaluation for Blind Attack Detection in LLM-based Evaluation Systems. IJCNLP-AACL (long papers) Lijia Liu, Takumi Kondo, Kyohei Atarashi, Koh Takeuchi, Jiyi Li, Shigeru Saito, Hisashi Kashima
2025	J	`jnl`	Counterfactual Evaluation for Blind Attack Detection in LLM-based Evaluation Systems. CoRR Lijia Liu, Takumi Kondo, Kyohei Atarashi, Koh Takeuchi, Jiyi Li, Shigeru Saito, Hisashi Kashima
2025	J	`jnl`	Dynamic Feature Selection from Variable Feature Sets Using Features of Features. CoRR Katsumi Takahashi, Koh Takeuchi, Hisashi Kashima
2025	J	`jnl`	Emulating Retrieval Augmented Generation via Prompt Engineering for Enhanced Long Context Comprehension in LLMs. CoRR Joon Park, Kyohei Atarashi, Koh Takeuchi, Hisashi Kashima
2025	J	`jnl`	Exploring Causes and Mitigation of Hallucinations in Large Vision Language Models. CoRR Yaqi Sun, Kyohei Atarashi, Koh Takeuchi, Hisashi Kashima
2025	A	`conf`	Federated Source-Free Domain Adaptation for Classification: Weighted Cluster Aggregation for Unlabeled Data. WACV Junki Mori, Kosuke Kihara, Taiki Miyagawa, Akinori F. Ebihara, Isamu Teranishi, Hisashi Kashima
2025	B	`conf`	Flexible Source-free Domain Generalization via Domain Prompt-Discriminator Collaborative Learning. IJCNN Yu Mitsuzumi, Akisato Kimura, Hisashi Kashima
2025	J	`jnl`	Hierarchical Text Classification Using Black Box Large Language Models. CoRR Kosuke Yoshimura, Hisashi Kashima
2025	A	`conf`	Learning Fair and Preferable Allocations through Neural Network. AAMAS Ryota Maruo, Koh Takeuchi, Hisashi Kashima
2025	J	`jnl`	Learning Location-Guided Time-Series Shapelets. IEEE Trans. Knowl. Data Eng. Akihiro Yamaguchi, Ken Ueno, Hisashi Kashima
2025	A	`conf`	Learning Neural Strategy-Proof Matching Mechanism from Examples. ECAI Ryota Maruo, Koh Takeuchi, Hisashi Kashima
2025	—	`conf`	Neural Double Auction Mechanism. ADMA (3) Tsuyoshi Suehara, Koh Takeuchi, Hisashi Kashima, Satoshi Oyama, Yuko Sakurai, Makoto Yokoo
2025	J	`jnl`	Robust Anomaly Detection Under Normality Distribution Shift in Dynamic Graphs. CoRR Xiaoyang Xu, Xiaofeng Lin, Koh Takeuchi, Kyohei Atarashi, Hisashi Kashima
2025	J	`jnl`	Scalable individual treatment effect estimator for large graphs. Mach. Learn. Xiaofeng Lin, Han Bao, Yan Cui, Koh Takeuchi, Hisashi Kashima
2025	J	`jnl`	Transfer learning with pre-trained conditional generative models. Mach. Learn. Shin'ya Yamaguchi, Sekitoshi Kanai, Atsutoshi Kumagai, Daiki Chijiwa, Hisashi Kashima
2025	—	`conf`	Treatment Effect Estimation for Graph-Structured Targets. PAKDD (6) Shonosuke Harada, Ryosuke Yoneda, Hisashi Kashima
2025	J	`jnl`	Unpacking the Implicit Norm Dynamics of Sharpness-Aware Minimization in Tensorized Models. CoRR Tianxiao Cao, Kyohei Atarashi, Hisashi Kashima
2025	J	`jnl`	XicorAttention: Time Series Transformer Using Attention with Nonlinear Correlation. CoRR Daichi Kimura, Tomonori Izumitani, Hisashi Kashima
2024	J	`jnl`	A Generalized Model for Multidimensional Intransitivity. CoRR Jiuding Duan, Jiyi Li, Yukino Baba, Hisashi Kashima
2024	—	`conf`	AHP-Powered LLM Reasoning for Multi-Criteria Evaluation of Open-Ended Responses. EMNLP (Findings) Xiaotian Lu, Jiyi Li, Koh Takeuchi, Hisashi Kashima
2024	J	`jnl`	AHP-Powered LLM Reasoning for Multi-Criteria Evaluation of Open-Ended Responses. CoRR Xiaotian Lu, Jiyi Li, Koh Takeuchi, Hisashi Kashima
2024	J	`jnl`	Cognitive Biases in Large Language Models: A Survey and Mitigation Experiments. CoRR Yasuaki Sumita, Koh Takeuchi, Hisashi Kashima
2024	B	`conf`	Efficient Preference Elicitation in Iterative Combinatorial Auctions with Many Participants. PRIMA Ryota Maruo, Hisashi Kashima
2024	J	`jnl`	Efficient Preference Elicitation in Iterative Combinatorial Auctions with Many Participants. CoRR Ryota Maruo, Hisashi Kashima
2024	A*	`conf`	Enhancing Chess Reinforcement Learning with Graph Representation. NeurIPS Tomas Rigaux, Hisashi Kashima
2024	J	`jnl`	Enhancing Chess Reinforcement Learning with Graph Representation. CoRR Tomas Rigaux, Hisashi Kashima
2024	—	`conf`	Evaluating Saliency Explanations in NLP by Crowdsourcing. LREC/COLING Xiaotian Lu, Jiyi Li, Zhen Wan, Xiaofeng Lin, Koh Takeuchi, Hisashi Kashima
2024	J	`jnl`	Evaluating Saliency Explanations in NLP by Crowdsourcing. CoRR Xiaotian Lu, Jiyi Li, Zhen Wan, Xiaofeng Lin, Koh Takeuchi, Hisashi Kashima
2024	J	`jnl`	Federated Source-free Domain Adaptation for Classification: Weighted Cluster Aggregation for Unlabeled Data. CoRR Junki Mori, Kosuke Kihara, Taiki Miyagawa, Akinori F. Ebihara, Isamu Teranishi, Hisashi Kashima
2024	J	`jnl`	InfoCEVAE: treatment effect estimation with hidden confounding variables matching. Mach. Learn. Shonosuke Harada, Hisashi Kashima
2024	A	`conf`	Learning Counterfactual Explanations with Intervals for Time-series Classification. CIKM Akihiro Yamaguchi, Ken Ueno, Ryusei Shingaki, Hisashi Kashima
2024	J	`jnl`	Learning Fair and Preferable Allocations through Neural Network. CoRR Ryota Maruo, Koh Takeuchi, Hisashi Kashima
2024	J	`jnl`	Learning Neural Strategy-Proof Matching Mechanism from Examples. CoRR Ryota Maruo, Koh Takeuchi, Hisashi Kashima
2024	J	`jnl`	Learning state importance for preference-based reinforcement learning. Mach. Learn. Guoxi Zhang, Hisashi Kashima
2024	J	`jnl`	Mitigating Cognitive Biases in Multi-Criteria Crowd Assessment. CoRR Shun Ito, Hisashi Kashima
2024	J	`jnl`	Neural Double Auction Mechanism. CoRR Tsuyoshi Suehara, Koh Takeuchi, Hisashi Kashima, Satoshi Oyama, Yuko Sakurai, Makoto Yokoo
2024	J	`jnl`	Online Policy Learning from Offline Preferences. CoRR Guoxi Zhang, Han Bao, Hisashi Kashima
2024	—	`conf`	Recovering Population Dynamics from a Single Point Cloud Snapshot. PAKDD (3) Yuki Wakai, Koh Takeuchi, Hisashi Kashima
2024	—	`conf`	Treatment Effect Estimation Under Unknown Interference. PAKDD (2) Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu, Hisashi Kashima
2024	J	`jnl`	Treatment Effect Estimation for Graph-Structured Targets. CoRR Shonosuke Harada, Ryosuke Yoneda, Hisashi Kashima
2024	J	`jnl`	Trustworthy human computation: a survey. Artif. Intell. Rev. Hisashi Kashima, Satoshi Oyama, Hiromi Arai, Junichiro Mori
2024	A*	`conf`	Understanding and Improving Source-Free Domain Adaptation from a Theoretical Perspective. CVPR Yu Mitsuzumi, Akisato Kimura, Hisashi Kashima
2023	—	`ed.`	Advances in Knowledge Discovery and Data Mining - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25-28, 2023, Proceedings, Part I PAKDD (1) Hisashi Kashima, Tsuyoshi Idé, Wen-Chih Peng
2023	—	`ed.`	Advances in Knowledge Discovery and Data Mining - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25-28, 2023, Proceedings, Part II PAKDD (2) Hisashi Kashima, Tsuyoshi Idé, Wen-Chih Peng
2023	—	`ed.`	Advances in Knowledge Discovery and Data Mining - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25-28, 2023, Proceedings, Part III PAKDD (3) Hisashi Kashima, Tsuyoshi Idé, Wen-Chih Peng
2023	—	`ed.`	Advances in Knowledge Discovery and Data Mining - 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25-28, 2023, Proceedings, Part IV PAKDD (4) Hisashi Kashima, Tsuyoshi Idé, Wen-Chih Peng
2023	A*	`conf`	Behavior Estimation from Multi-Source Data for Offline Reinforcement Learning. AAAI Guoxi Zhang, Hisashi Kashima
2023	A*	`conf`	Causal Effect Estimation on Hierarchical Spatial Graph Data. KDD Koh Takeuchi, Ryo Nishida, Hisashi Kashima, Masaki Onishi
2023	C	`conf`	Deep Knowledge Tracing is an implicit dynamic multidimensional item response theory model. ICCE Jill-Jênn Vie, Hisashi Kashima
2023	J	`jnl`	Deep Knowledge Tracing is an implicit dynamic multidimensional item response theory model. CoRR Jill-Jênn Vie, Hisashi Kashima
2023	—	`conf`	Estimating Treatment Effects Under Heterogeneous Interference. ECML/PKDD (1) Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu, Han Bao, Koh Takeuchi, Hisashi Kashima
2023	J	`jnl`	Estimating Treatment Effects Under Heterogeneous Interference. CoRR Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu, Han Bao, Koh Takeuchi, Hisashi Kashima
2023	—	`conf`	Label Selection Approach to Learning from Crowds. ICONIP (8) Kosuke Yoshimura, Hisashi Kashima
2023	J	`jnl`	Label Selection Approach to Learning from Crowds. CoRR Kosuke Yoshimura, Hisashi Kashima
2023	J	`jnl`	Making individually fair predictions with causal pathways. Data Min. Knowl. Discov. Yoichi Chikahara, Shinsaku Sakaue, Akinori Fujino, Hisashi Kashima
2023	J	`jnl`	Mitigating Observation Biases in Crowdsourced Label Aggregation. CoRR Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima
2023	C	`conf`	Mitigating Voter Attribute Bias for Fair Opinion Aggregation. AIES Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima
2023	J	`jnl`	Mitigating Voter Attribute Bias for Fair Opinion Aggregation. CoRR Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima
2023	A*	`conf`	Multiview Representation Learning from Crowdsourced Triplet Comparisons. WWW Xiaotian Lu, Jiyi Li, Koh Takeuchi, Hisashi Kashima
2023	J	`jnl`	Multiview Representation Learning from Crowdsourced Triplet Comparisons. CoRR Xiaotian Lu, Jiyi Li, Koh Takeuchi, Hisashi Kashima
2023	A*	`conf`	QTNet: Theory-based Queue Length Prediction for Urban Traffic. KDD Ryu Shirakami, Toshiya Kitahara, Koh Takeuchi, Hisashi Kashima
2023	A*	`conf`	Regularizing Neural Networks with Meta-Learning Generative Models. NeurIPS Shin'ya Yamaguchi, Daiki Chijiwa, Sekitoshi Kanai, Atsutoshi Kumagai, Hisashi Kashima
2023	J	`jnl`	Regularizing Neural Networks with Meta-Learning Generative Models. CoRR Shin'ya Yamaguchi, Daiki Chijiwa, Sekitoshi Kanai, Atsutoshi Kumagai, Hisashi Kashima
2023	A	`conf`	Time-series Shapelets with Learnable Lengths. CIKM Akihiro Yamaguchi, Ken Ueno, Hisashi Kashima
2022	—	`ed.`	Advances in Artificial Intelligence - Selected Papers from the Annual Conference of Japanese Society of Artificial Intelligence, JSAI 2021, Virtual Event, Japan, 8-11 June 2021 JSAI Yasufumi Takama, Naohiro Matsumura, Katsutoshi Yada, Mitsunori Matsushita, Daisuke Katagami, Akinori Abe, Hisashi Kashima, Toshihiro Hiraoka, Takahiro Uchiya, Rafal Rzepka
2022	—	`conf`	Batch Reinforcement Learning from Crowds. ECML/PKDD (4) Guoxi Zhang, Hisashi Kashima
2022	J	`jnl`	Bayesian optimization with partially specified queries. Mach. Learn. Shogo Hayashi, Junya Honda, Hisashi Kashima
2022	J	`jnl`	Behavior Estimation from Multi-Source Data for Offline Reinforcement Learning. CoRR Guoxi Zhang, Hisashi Kashima
2022	J	`jnl`	Constant Time Graph Neural Networks. ACM Trans. Knowl. Discov. Data Ryoma Sato, Makoto Yamada, Hisashi Kashima
2022	J	`jnl`	Context-aware spatio-temporal event prediction via convolutional Hawkes processes. Mach. Learn. Maya Okawa, Tomoharu Iwata, Yusuke Tanaka, Takeshi Kurashima, Hiroyuki Toda, Hisashi Kashima
2022	J	`jnl`	Feature Selection for Discovering Distributional Treatment Effect Modifiers. CoRR Yoichi Chikahara, Makoto Yamada, Hisashi Kashima
2022	A	`conf`	Feature selection for discovering distributional treatment effect modifiers. UAI Yoichi Chikahara, Makoto Yamada, Hisashi Kashima
2022	B	`conf`	Improving Pairwise Rank Aggregation via Querying for Rank Difference. DSAA Guoxi Zhang, Jiyi Li, Hisashi Kashima
2022	J	`jnl`	Improving imbalanced classification using near-miss instances. Expert Syst. Appl. Akira Tanimoto, So Yamada, Takashi Takenouchi, Masashi Sugiyama, Hisashi Kashima
2022	A*	`conf`	Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations. AAAI Sein Minn, Jill-Jênn Vie, Koh Takeuchi, Hisashi Kashima, Feida Zhu
2022	A*	`conf`	Learning Evolvable Time-series Shapelets. ICDE Akihiro Yamaguchi, Ken Ueno, Hisashi Kashima
2022	A*	`conf`	Learning Optimal Priors for Task-Invariant Representations in Variational Autoencoders. KDD Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Sekitoshi Kanai, Masanori Yamada, Yuki Yamanaka, Hisashi Kashima
2022	A	`conf`	Learning Time-series Shapelets Enhancing Discriminability. SDM Akihiro Yamaguchi, Ken Ueno, Hisashi Kashima
2022	B	`conf`	Mitigating Observation Biases in Crowdsourced Label Aggregation. ICPR Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima
2022	J	`jnl`	Poincare: Recommending Publication Venues via Treatment Effect Estimation. J. Informetrics Ryoma Sato, Makoto Yamada, Hisashi Kashima
2022	A*	`conf`	Re-evaluating Word Mover's Distance. ICML Ryoma Sato, Makoto Yamada, Hisashi Kashima
2022	J	`jnl`	Transfer Learning with Pre-trained Conditional Generative Models. CoRR Shin'ya Yamaguchi, Sekitoshi Kanai, Atsutoshi Kumagai, Daiki Chijiwa, Hisashi Kashima
2022	J	`jnl`	Trustworthy Human Computation: A Survey. CoRR Hisashi Kashima, Satoshi Oyama, Hiromi Arai, Junichiro Mori
2022	A	`conf`	Twin Papers: A Simple Framework of Causal Inference for Citations via Coupling. CIKM Ryoma Sato, Makoto Yamada, Hisashi Kashima
2022	J	`jnl`	Twin Papers: A Simple Framework of Causal Inference for Citations via Coupling. CoRR Ryoma Sato, Makoto Yamada, Hisashi Kashima
2022	B	`conf`	Variational Factorization Machines for Preference Elicitation in Large-Scale Recommender Systems. IEEE Big Data Jill-Jênn Vie, Tomas Rigaux, Hisashi Kashima
2022	J	`jnl`	Variational Factorization Machines for Preference Elicitation in Large-Scale Recommender Systems. CoRR Jill-Jênn Vie, Tomas Rigaux, Hisashi Kashima
2021	—	`ed.`	Advances in Artificial Intelligence - Selected Papers from the Annual Conference of Japanese Society of Artificial Intelligence, JSAI 2020, Kumamoto-ken, Japan, 9-12 June 2020. JSAI Katsutoshi Yada, Daisuke Katagami, Yasufumi Takama, Takayuki Ito, Akinori Abe, Eri Sato-Shimokawara, Junichiro Mori, Naohiro Matsumura, Hisashi Kashima
2021	J	`jnl`	Batch Reinforcement Learning from Crowds. CoRR Guoxi Zhang, Hisashi Kashima
2021	—	`conf`	Causal Combinatorial Factorization Machines for Set-Wise Recommendation. PAKDD (2) Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima
2021	—	`conf`	Computationally Efficient Wasserstein Loss for Structured Labels. EACL (Student Research Workshop) Ayato Toyokuni, Sho Yokoi, Hisashi Kashima, Makoto Yamada
2021	J	`jnl`	Computationally Efficient Wasserstein Loss for Structured Labels. CoRR Ayato Toyokuni, Sho Yokoi, Hisashi Kashima, Makoto Yamada
2021	—	`conf`	Crowdsourcing Evaluation of Saliency-Based XAI Methods. ECML/PKDD (5) Xiaotian Lu, Arseny Tolmachev, Tatsuya Yamamoto, Koh Takeuchi, Seiji Okajima, Tomoyoshi Takebayashi, Koji Maruhashi, Hisashi Kashima
2021	J	`jnl`	Crowdsourcing Evaluation of Saliency-based XAI Methods. CoRR Xiaotian Lu, Arseny Tolmachev, Tatsuya Yamamoto, Koh Takeuchi, Seiji Okajima, Tomoyoshi Takebayashi, Koji Maruhashi, Hisashi Kashima
2021	A*	`conf`	Dynamic Hawkes Processes for Discovering Time-evolving Communities' States behind Diffusion Processes. KDD Maya Okawa, Tomoharu Iwata, Yusuke Tanaka, Hiroyuki Toda, Takeshi Kurashima, Hisashi Kashima
2021	J	`jnl`	Dynamic Hawkes Processes for Discovering Time-evolving Communities' States behind Diffusion Processes. CoRR Maya Okawa, Tomoharu Iwata, Yusuke Tanaka, Hiroyuki Toda, Takeshi Kurashima, Hisashi Kashima
2021	A	`conf`	Grab the Reins of Crowds: Estimating the Effects of Crowd Movement Guidance Using Causal Inference. AAMAS Koh Takeuchi, Ryo Nishida, Hisashi Kashima, Masaki Onishi
2021	A	`conf`	GraphITE: Estimating Individual Effects of Graph-structured Treatments. CIKM Shonosuke Harada, Hisashi Kashima
2021	—	`conf`	In-Vehicle Network Attack Detection Across Vehicle Models: A Supervised-Unsupervised Hybrid Approach. ITSC Shu Nakamura, Koh Takeuchi, Hisashi Kashima, Takeshi Kishikawa, Takashi Ushio, Tomoyuki Haga, Takamitsu Sasaki
2021	—	`conf`	Inter-domain Multi-relational Link Prediction. ECML/PKDD (2) Luu Huu Phuc, Koh Takeuchi, Seiji Okajima, Arseny Tolmachev, Tomoyoshi Takebayashi, Koji Maruhashi, Hisashi Kashima
2021	J	`jnl`	Inter-domain Multi-relational Link Prediction. CoRR Luu Huu Phuc, Koh Takeuchi, Seiji Okajima, Arseny Tolmachev, Tomoyoshi Takebayashi, Koji Maruhashi, Hisashi Kashima
2021	J	`jnl`	Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations. CoRR Sein Minn, Jill-Jênn Vie, Koh Takeuchi, Hisashi Kashima, Feida Zhu
2021	—	`conf`	Label Aggregation for Crowdsourced Triplet Similarity Comparisons. ICONIP (6) Jiyi Li, Lucas Ryo Endo, Hisashi Kashima
2021	A	`conf`	Learning Individually Fair Classifier with Path-Specific Causal-Effect Constraint. AISTATS Yoichi Chikahara, Shinsaku Sakaue, Akinori Fujino, Hisashi Kashima
2021	J	`jnl`	Learning to Rank for Multi-Step Ahead Time-Series Forecasting. IEEE Access Jiuding Duan, Hisashi Kashima
2021	—	`conf`	Preliminary Experiments to Examine the Stability of Bias-Aware Techniques. BIAS Toshihiro Kamishima, Shotaro Akaho, Yukino Baba, Hisashi Kashima
2021	A	`conf`	Random Features Strengthen Graph Neural Networks. SDM Ryoma Sato, Makoto Yamada, Hisashi Kashima
2021	J	`jnl`	Re-evaluating Word Mover's Distance. CoRR Ryoma Sato, Makoto Yamada, Hisashi Kashima
2021	A	`conf`	Regret Minimization for Causal Inference on Large Treatment Space. AISTATS Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima
2020	B	`conf`	An Intransitivity Model for Matchup and Pairwise Comparison. ICPR Yan Gu, Jiuding Duan, Hisashi Kashima
2020	J	`jnl`	Chemical Property Prediction Under Experimental Biases. CoRR Yang Liu, Hisashi Kashima
2020	J	`jnl`	Counterfactual Propagation for Semi-Supervised Individual Treatment Effect Estimation. CoRR Shonosuke Harada, Hisashi Kashima
2020	—	`conf`	Counterfactual Propagation for Semi-supervised Individual Treatment Effect Estimation. ECML/PKDD (1) Shonosuke Harada, Hisashi Kashima
2020	B	`conf`	CrowDEA: Multi-View Idea Prioritization with Crowds. HCOMP Yukino Baba, Jiyi Li, Hisashi Kashima
2020	J	`jnl`	CrowDEA: Multi-view Idea Prioritization with Crowds. CoRR Yukino Baba, Jiyi Li, Hisashi Kashima
2020	J	`jnl`	Dual graph convolutional neural network for predicting chemical networks. BMC Bioinform. Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki, Yukino Baba, Ichigaku Takigawa, Yoshihiro Yamanishi, Hisashi Kashima
2020	A*	`conf`	Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance. ICML Yasutoshi Ida, Sekitoshi Kanai, Yasuhiro Fujiwara, Tomoharu Iwata, Koh Takeuchi, Hisashi Kashima
2020	J	`jnl`	Fast Unbalanced Optimal Transport on Tree. CoRR Ryoma Sato, Makoto Yamada, Hisashi Kashima
2020	A*	`conf`	Fast Unbalanced Optimal Transport on a Tree. NeurIPS Ryoma Sato, Makoto Yamada, Hisashi Kashima
2020	J	`jnl`	Fast and Robust Comparison of Probability Measures in Heterogeneous Spaces. CoRR Ryoma Sato, Marco Cuturi, Makoto Yamada, Hisashi Kashima
2020	J	`jnl`	GraphITE: Estimating Individual Effects of Graph-structured Treatments. CoRR Shonosuke Harada, Hisashi Kashima
2020	A*	`conf`	Performance as a Constraint: An Improved Wisdom of Crowds Using Performance Regularization. IJCAI Jiyi Li, Yasushi Kawase, Yukino Baba, Hisashi Kashima
2020	J	`jnl`	Poincare: Recommending Publication Venues via Treatment Effect Estimation. CoRR Ryoma Sato, Makoto Yamada, Hisashi Kashima
2020	J	`jnl`	Random Features Strengthen Graph Neural Networks. CoRR Ryoma Sato, Makoto Yamada, Hisashi Kashima
2020	J	`jnl`	Regret Minimization for Causal Inference on Large Treatment Space. CoRR Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima
2020	B	`conf`	Simultaneous Link Prediction on Unaligned Networks Using Graph Embedding and Optimal Transport. DSAA Luu Huu Phuc, Koh Takeuchi, Makoto Yamada, Hisashi Kashima
2020	B	`conf`	Stress Prediction from Head Motion. DSAA Hitoshi Kusano, Yuji Horiguchi, Yukino Baba, Hisashi Kashima
2020	J	`jnl`	Synthetic accessibility assessment using auxiliary responses. Expert Syst. Appl. Shun Ito, Yukino Baba, Tetsu Isomura, Hisashi Kashima
2020	A	`conf`	Topological Bayesian Optimization with Persistence Diagrams. ECAI Tatsuya Shiraishi, Tam Le, Hisashi Kashima, Makoto Yamada
2019	C	`conf`	Active Change-Point Detection. ACML Shogo Hayashi, Yoshinobu Kawahara, Hisashi Kashima
2019	A*	`conf`	Approximation Ratios of Graph Neural Networks for Combinatorial Problems. NeurIPS Ryoma Sato, Makoto Yamada, Hisashi Kashima
2019	J	`jnl`	Approximation Ratios of Graph Neural Networks for Combinatorial Problems. CoRR Ryoma Sato, Makoto Yamada, Hisashi Kashima
2019	J	`jnl`	Constant Time Graph Neural Networks. CoRR Ryoma Sato, Makoto Yamada, Hisashi Kashima
2019	—	`conf`	Context-Regularized Neural Collaborative Filtering for Game App Recommendation. RecSys (Late-Breaking Results) Shonosuke Harada, Kazuki Taniguchi, Makoto Yamada, Hisashi Kashima
2019	Misc	`conf`	Crownn: Human-in-the-loop Network with Crowd-generated Inputs. ICASSP Yusuke Sakata, Yukino Baba, Hisashi Kashima
2019	A*	`conf`	Fast Sparse Group Lasso. NeurIPS Yasutoshi Ida, Yasuhiro Fujiwara, Hisashi Kashima
2019	—	`conf`	In-Vehicle Network Intrusion Detection and Explanation Using Density Ratio Estimation. ITSC Daiki Tanaka, Makoto Yamada, Hisashi Kashima, Takeshi Kishikawa, Tomoyuki Haga, Takamitsu Sasaki
2019	—	`conf`	Interdependence Model for Multi-label Classification. ICANN (4) Kosuke Yoshimura, Tomoaki Iwase, Yukino Baba, Hisashi Kashima
2019	A*	`conf`	Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing. AAAI Jill-Jênn Vie, Hisashi Kashima
2019	B	`conf`	Large-scale Driver Identification Using Automobile Driving Data. SMC Daiki Tanaka, Yukino Baba, Hisashi Kashima, Yuta Okubo
2019	J	`jnl`	Learning to Find Hard Instances of Graph Problems. CoRR Ryoma Sato, Makoto Yamada, Hisashi Kashima
2019	C	`conf`	Learning to Sample Hard Instances for Graph Algorithms. ACML Ryoma Sato, Makoto Yamada, Hisashi Kashima
2019	B	`conf`	Long-Term Prediction of Small Time-Series Data Using Generalized Distillation. IJCNN Shogo Hayashi, Akira Tanimoto, Hisashi Kashima
2019	B	`conf`	Probabilistic Modeling of Peer Correction and Peer Assessment. EDM Takeru Sunahase, Yukino Baba, Hisashi Kashima
2019	A*	`conf`	Theoretical evidence for adversarial robustness through randomization. NeurIPS Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric Gouy-Pailler, Jamal Atif
2019	J	`jnl`	Theoretical evidence for adversarial robustness through randomization: the case of the Exponential family. CoRR Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric Gouy-Pailler, Jamal Atif
2019	J	`jnl`	Topological Bayesian Optimization with Persistence Diagrams. CoRR Tatsuya Shiraishi, Tam Le, Hisashi Kashima, Makoto Yamada
2018	A*	`conf`	AdaFlock: Adaptive Feature Discovery for Human-in-the-loop Predictive Modeling. AAAI Ryusuke Takahama, Yukino Baba, Nobuyuki Shimizu, Sumio Fujita, Hisashi Kashima
2018	—	`conf`	BayesGrad: Explaining Predictions of Graph Convolutional Networks. ICONIP (5) Hirotaka Akita, Kosuke Nakago, Tomoki Komatsu, Yohei Sugawara, Shin-ichi Maeda, Yukino Baba, Hisashi Kashima
2018	J	`jnl`	BayesGrad: Explaining Predictions of Graph Convolutional Networks. CoRR Hirotaka Akita, Kosuke Nakago, Tomoki Komatsu, Yohei Sugawara, Shin-ichi Maeda, Yukino Baba, Hisashi Kashima
2018	A*	`conf`	Data Analysis Competition Platform for Educational Purposes: Lessons Learned and Future Challenges. AAAI Yukino Baba, Tomoumi Takase, Kyohei Atarashi, Satoshi Oyama, Hisashi Kashima
2018	J	`jnl`	Dual Convolutional Neural Network for Graph of Graphs Link Prediction. CoRR Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki, Yukino Baba, Ichigaku Takigawa, Yoshihiro Yamanishi, Hisashi Kashima
2018	—	`conf`	Incorporating Worker Similarity for Label Aggregation in Crowdsourcing. ICANN (2) Jiyi Li, Yukino Baba, Hisashi Kashima
2018	J	`jnl`	Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing. CoRR Jill-Jênn Vie, Hisashi Kashima
2018	—	`conf`	On Reducing Dimensionality of Labeled Data Efficiently. PAKDD (3) Guoxi Zhang, Tomoharu Iwata, Hisashi Kashima
2018	—	`conf`	Payload-Based Statistical Intrusion Detection for In-Vehicle Networks. PAKDD (Workshops) Takuya Kuwahara, Yukino Baba, Hisashi Kashima, Takeshi Kishikawa, Jun'ichi Tsurumi, Tomoyuki Haga, Yoshihiro Ujiie, Takamitsu Sasaki, Hideki Matsushima
2018	A*	`conf`	Predictive Modeling of Learning Continuation in Preschool Education Using Temporal Patterns of Development Tests. AAAI Junpei Naito, Yukino Baba, Hisashi Kashima, Takenori Takaki, Takuya Funo
2018	—	`conf`	Short-Term Precipitation Prediction with Skip-Connected PredNet. ICANN (3) Ryoma Sato, Hisashi Kashima, Takehiro Yamamoto
2018	A*	`conf`	Simultaneous Clustering and Ranking from Pairwise Comparisons. IJCAI Jiyi Li, Yukino Baba, Hisashi Kashima
2018	J	`jnl`	Supervised and Unsupervised Intrusion Detection Based on CAN Message Frequencies for In-vehicle Network. J. Inf. Process. Takuya Kuwahara, Yukino Baba, Hisashi Kashima, Takeshi Kishikawa, Jun'ichi Tsurumi, Tomoyuki Haga, Yoshihiro Ujiie, Takamitsu Sasaki, Hideki Matsushima
2017	—	`conf`	A Generalized Model for Multidimensional Intransitivity. PAKDD (2) Jiuding Duan, Jiyi Li, Yukino Baba, Hisashi Kashima
2017	—	`conf`	Atomic Distance Kernel for Material Property Prediction. ICONIP (1) Hirotaka Akita, Yukino Baba, Hisashi Kashima, Atsuto Seko
2017	A*	`conf`	Autoregressive Tensor Factorization for Spatio-Temporal Predictions. ICDM Koh Takeuchi, Hisashi Kashima, Naonori Ueda
2017	—	`conf`	Distributed Multi-task Learning for Sensor Network. ECML/PKDD (2) Jiyi Li, Tomohiro Arai, Yukino Baba, Hisashi Kashima, Shotaro Miwa
2017	A	`conf`	Hyper Questions: Unsupervised Targeting of a Few Experts in Crowdsourcing. CIKM Jiyi Li, Yukino Baba, Hisashi Kashima
2017	—	`conf`	Iterative Reduction Worker Filtering for Crowdsourced Label Aggregation. WISE (2) Jiyi Li, Hisashi Kashima
2017	A*	`conf`	Learning Implicit Tasks for Patient-Specific Risk Modeling in ICU. AAAI Nozomi Nori, Hisashi Kashima, Kazuto Yamashita, Susumu Kunisawa, Yuichi Imanaka
2017	J	`jnl`	Link Prediction in Sparse Networks by Incidence Matrix Factorization. J. Inf. Process. Sho Yokoi, Hiroshi Kajino, Hisashi Kashima
2017	A*	`conf`	Pairwise HITS: Quality Estimation from Pairwise Comparisons in Creator-Evaluator Crowdsourcing Process. AAAI Takeru Sunahase, Yukino Baba, Hisashi Kashima
2017	A*	`conf`	Predicting Fuel Consumption and Flight Delays for Low-Cost Airlines. AAAI Yuji Horiguchi, Yukino Baba, Hisashi Kashima, Masahito Suzuki, Hiroki Kayahara, Jun Maeno
2017	—	`conf`	Quality Control for Crowdsourced Multi-label Classification Using RAkEL. ICONIP (1) Kosuke Yoshimura, Yukino Baba, Hisashi Kashima
2017	—	`conf`	Robust Multi-view Topic Modeling by Incorporating Detecting Anomalies. ECML/PKDD (2) Guoxi Zhang, Tomoharu Iwata, Hisashi Kashima
2017	—	`conf`	Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario. MANPU@ICDAR Jill-Jênn Vie, Florian Yger, Ryan Lahfa, Basile Clement, Kévin Cocchi, Thomas Chalumeau, Hisashi Kashima
2017	J	`jnl`	Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario. CoRR Jill-Jênn Vie, Florian Yger, Ryan Lahfa, Basile Clement, Kévin Cocchi, Thomas Chalumeau, Hisashi Kashima
2016	—	`conf`	Budgeted stream-based active learning via adaptive submodular maximization. NIPS Kaito Fujii, Hisashi Kashima
2016	J	`jnl`	Crowdsourcing chart digitizer: task design and quality control for making legacy open data machine-readable. Int. J. Data Sci. Anal. Satoshi Oyama, Yukino Baba, Ikki Ohmukai, Hiroaki Dokoshi, Hisashi Kashima
2016	—	`conf`	Learning to Enumerate. ICANN (1) Patrick Jörger, Yukino Baba, Hisashi Kashima
2016	A	`conf`	Link Prediction by Incidence Matrix Factorization. ECAI Sho Yokoi, Hiroshi Kajino, Hisashi Kashima
2016	J	`jnl`	Participation recommendation system for crowdsourcing contests. Expert Syst. Appl. Yukino Baba, Kei Kinoshita, Hisashi Kashima
2016	A*	`conf`	Progressive Comparison for Ranking Estimation. IJCAI Ryusuke Takahama, Toshihiro Kamishima, Hisashi Kashima
2016	J	`jnl`	Quality control of crowdsourced classification using hierarchical class structures. Expert Syst. Appl. Naoki Otani, Yukino Baba, Hisashi Kashima
2015	B	`conf`	From one star to three stars: Upgrading legacy open data using crowdsourcing. DSAA Satoshi Oyama, Yukino Baba, Ikki Ohmukai, Hiroaki Dokoshi, Hisashi Kashima
2015	A*	`conf`	Predictive Approaches for Low-Cost Preventive Medicine Program in Developing Countries. KDD Yukino Baba, Hisashi Kashima, Yasunobu Nohara, Eiko Kai, Partha Pratim Ghosh, Rafiqul Islam Maruf, 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
2015	A*	`conf`	Quality Control for Crowdsourced Hierarchical Classification. ICDM Naoki Otani, Yukino Baba, Hisashi Kashima
2015	—	`conf`	Quality Control for Crowdsourced POI Collection. PAKDD (2) Shunsuke Kajimura, Yukino Baba, Hiroshi Kajino, Hisashi Kashima
2015	B	`conf`	Quantum Energy Prediction Using Graph Kernel. SMC Jiuding Duan, Atsuto Seko, Hisashi Kashima
2015	A*	`conf`	Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem. COLT Junpei Komiyama, Junya Honda, Hisashi Kashima, Hiroshi Nakagawa
2015	J	`jnl`	Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem. CoRR Junpei Komiyama, Junya Honda, Hisashi Kashima, Hiroshi Nakagawa
2015	A*	`conf`	Simultaneous Modeling of Multiple Diseases for Mortality Prediction in Acute Hospital Care. KDD Nozomi Nori, Hisashi Kashima, Kazuto Yamashita, Hiroshi Ikai, Yuichi Imanaka
2014	—	`conf`	A Label Completion Approach to Crowd Approximation. ICONIP (2) Toshihiro Watanabe, Hisashi Kashima
2014	—	`conf`	Crowdordering. PAKDD (2) Toshiko Matsui, Yukino Baba, Toshihiro Kamishima, Hisashi Kashima
2014	B	`conf`	Crowdsourced Data Analytics: A Case Study of a Predictive Modeling Competition. HCOMP Yukino Baba, Nozomi Nori, Shigeru Saito, Hisashi Kashima
2014	B	`conf`	Crowdsourced data analytics: A case study of a predictive modeling competition. DSAA Yukino Baba, Nozomi Nori, Shigeru Saito, Hisashi Kashima
2014	B	`conf`	Instance-Privacy Preserving Crowdsourcing. HCOMP Hiroshi Kajino, Yukino Baba, Hisashi Kashima
2014	A*	`conf`	Latent Confusion Analysis by Normalized Gamma Construction. ICML Issei Sato, Hisashi Kashima, Hiroshi Nakagawa
2014	—	`conf`	Learning an accurate entity resolution model from crowdsourced labels. ICUIMC Jingjing Wang, Satoshi Oyama, Masahito Kurihara, Hisashi Kashima
2014	J	`jnl`	Leveraging non-expert crowdsourcing workers for improper task detection in crowdsourcing marketplaces. Expert Syst. Appl. Yukino Baba, Hisashi Kashima, Kei Kinoshita, Goushi Yamaguchi, Yosuke Akiyoshi
2014	J	`jnl`	Preserving worker privacy in crowdsourcing. Data Min. Knowl. Discov. Hiroshi Kajino, Hiromi Arai, Hisashi Kashima
2014	B	`conf`	Quality Control for Crowdsourced Enumeration Tasks. HCOMP Shunsuke Kajimura, Yukino Baba, Hiroshi Kajino, Hisashi Kashima
2014	Misc	`conf`	Steered crowdsensing: incentive design towards quality-oriented place-centric crowdsensing. UbiComp Ryoma Kawajiri, Masamichi Shimosaka, Hisashi Kashima
2013	A*	`conf`	Accurate Integration of Crowdsourced Labels Using Workers' Self-reported Confidence Scores. IJCAI Satoshi Oyama, Yukino Baba, Yuko Sakurai, Hisashi Kashima
2013	A*	`conf`	Clustering Crowds. AAAI Hiroshi Kajino, Yuta Tsuboi, Hisashi Kashima
2013	—	`conf`	Crowdsourcing Quality Control for Item Ordering Tasks. HCOMP (Works in Progress / Demos) Toshiko Matsui, Yukino Baba, Toshihiro Kamishima, Hisashi Kashima
2013	—	`conf`	EM-Based Inference of True Labels Using Confidence Judgments. HCOMP (Works in Progress / Demos) Satoshi Oyama, Yukino Baba, Yuko Sakurai, Hisashi Kashima
2013	J	`jnl`	Fast Iterative Mining Using Sparsity-Inducing Loss Functions. IEICE Trans. Inf. Syst. Hiroto Saigo, Hisashi Kashima, Koji Tsuda
2013	J	`jnl`	Large-Scale Personalized Human Activity Recognition Using Online Multitask Learning. IEEE Trans. Knowl. Data Eng. Xu Sun, Hisashi Kashima, Naonori Ueda
2013	C	`conf`	Leveraging Crowdsourcing to Detect Improper Tasks in Crowdsourcing Marketplaces. IAAI Yukino Baba, Hisashi Kashima, Kei Kinoshita, Goushi Yamaguchi, Yosuke Akiyoshi
2013	—	`conf`	Matrix Factorization With Aggregated Observations. PAKDD (2) Yoshifumi Aimoto, Hisashi Kashima
2013	—	`conf`	Statistical Quality Estimation for General Crowdsourcing Tasks. HCOMP (Works in Progress / Demos) Yukino Baba, Hisashi Kashima
2013	A*	`conf`	Statistical quality estimation for general crowdsourcing tasks. KDD Yukino Baba, Hisashi Kashima
2012	A*	`conf`	A Convex Formulation for Learning from Crowds. AAAI Hiroshi Kajino, Yuta Tsuboi, Hisashi Kashima
2012	J	`jnl`	Fast Computation of Subpath Kernel for Trees CoRR Daisuke Kimura, Hisashi Kashima
2012	A*	`conf`	Fast Computation of Subpath Kernel for Trees. ICML Daisuke Kimura, Hisashi Kashima
2012	B	`conf`	Fast Similarity Computation in Factorized Tensors. SISAP Michael E. Houle, Hisashi Kashima, Michael Nett
2012	—	`conf`	Generalized Expansion Dimension. ICDM Workshops Michael E. Houle, Hisashi Kashima, Michael Nett
2012	B	`conf`	Hash-based structural similarity for semi-supervised Learning on attribute graphs. ICPR Shohei Hido, Hisashi Kashima
2012	—	`conf`	Learning from Crowds and Experts. HCOMP@AAAI Hiroshi Kajino, Yuta Tsuboi, Issei Sato, Hisashi Kashima
2012	J	`jnl`	Link Prediction Across Time via Cross-Temporal Locality Preserving Projections. IEICE Trans. Inf. Syst. Satoshi Oyama, Kohei Hayashi, Hisashi Kashima
2012	J	`jnl`	Machine learning approach for finding business partners and building reciprocal relationships. Expert Syst. Appl. Junichiro Mori, Yuya Kajikawa, Hisashi Kashima, Ichiro Sakata
2012	A*	`conf`	Multinomial Relation Prediction in Social Data: A Dimension Reduction Approach. AAAI Nozomi Nori, Danushka Bollegala, Hisashi Kashima
2012	J	`jnl`	Parametric Return Density Estimation for Reinforcement Learning CoRR Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya, Toshiyuki Tanaka
2012	—	`ed.`	Pattern Recognition in Bioinformatics - 7th IAPR International Conference, PRIB 2012, Tokyo, Japan, November 8-10, 2012. Proceedings PRIB Tetsuo Shibuya, Hisashi Kashima, Jun Sese, Shandar Ahmad
2012	—	`conf`	Self-measuring Similarity for Multi-task Gaussian Process. ICML Unsupervised and Transfer Learning Kohei Hayashi, Takashi Takenouchi, Ryota Tomioka, Hisashi Kashima
2012	J	`jnl`	Tensor factorization using auxiliary information. Data Min. Knowl. Discov. Atsuhiro Narita, Kohei Hayashi, Ryota Tomioka, Hisashi Kashima
2011	A*	`conf`	A New Multi-task Learning Method for Personalized Activity Recognition. ICDM Xu Sun, Hisashi Kashima, Ryota Tomioka, Naonori Ueda, Ping Li
2011	—	`conf`	A Subpath Kernel for Rooted Unordered Trees. PAKDD (1) Daisuke Kimura, Tetsuji Kuboyama, Tetsuo Shibuya, Hisashi Kashima
2011	A*	`conf`	Cross-Temporal Link Prediction. ICDM Satoshi Oyama, Kohei Hayashi, Hisashi Kashima
2011	A*	`conf`	Fast Newton-CG Method for Batch Learning of Conditional Random Fields. AAAI Yuta Tsuboi, Yuya Unno, Hisashi Kashima, Naoaki Okazaki
2011	—	`conf`	Large Scale Real-Life Action Recognition Using Conditional Random Fields with Stochastic Training. PAKDD (2) Xu Sun, Hisashi Kashima, Ryota Tomioka, Naonori Ueda
2011	—	`conf`	Statistical Performance of Convex Tensor Decomposition. NIPS Ryota Tomioka, Taiji Suzuki, Kohei Hayashi, Hisashi Kashima
2011	J	`jnl`	Statistical outlier detection using direct density ratio estimation. Knowl. Inf. Syst. Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi Sugiyama, Takafumi Kanamori
2011	—	`conf`	Tensor Factorization Using Auxiliary Information. ECML/PKDD (2) Atsuhiro Narita, Kohei Hayashi, Ryota Tomioka, Hisashi Kashima
2010	A*	`conf`	A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices. ICML Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama, Hisashi Kashima
2010	J	`jnl`	A Transfer Learning Approach and Selective Integration of Multiple Types of Assays for Biological Network Inference. Int. J. Knowl. Discov. Bioinform. Tsuyoshi Kato, Kinya Okada, Hisashi Kashima, Masashi Sugiyama
2010	A*	`conf`	Averaged Stochastic Gradient Descent with Feedback: An Accurate, Robust, and Fast Training Method. ICDM Xu Sun, Hisashi Kashima, Takuya Matsuzaki, Naonori Ueda
2010	J	`jnl`	Cartesian Kernel: An Efficient Alternative to the Pairwise Kernel. IEICE Trans. Inf. Syst. Hisashi Kashima, Satoshi Oyama, Yoshihiro Yamanishi, Koji Tsuda
2010	J	`jnl`	Conic Programming for Multitask Learning. IEEE Trans. Knowl. Data Eng. Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, Kiyoshi Asai
2010	—	`conf`	Fast and Scalable Algorithms for Semi-supervised Link Prediction on Static and Dynamic Graphs. ECML/PKDD (3) Rudy Raymond, Hisashi Kashima
2010	—	`conf`	Finding Itemset-Sharing Patterns in a Large Itemset-Associated Graph. PAKDD (2) Mutsumi Fukuzaki, Mio Seki, Hisashi Kashima, Jun Sese
2010	J	`jnl`	Least Absolute Policy Iteration-A Robust Approach to Value Function Approximation. IEICE Trans. Inf. Syst. Masashi Sugiyama, Hirotaka Hachiya, Hisashi Kashima, Tetsuro Morimura
2010	A*	`conf`	Nonparametric Return Distribution Approximation for Reinforcement Learning. ICML Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya, Toshiyuki Tanaka
2010	A	`conf`	Parametric Return Density Estimation for Reinforcement Learning. UAI Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya, Toshiyuki Tanaka
2010	J	`jnl`	Protein complex prediction via verifying and reconstructing the topology of domain-domain interactions. BMC Bioinform. Yosuke Ozawa, Rintaro Saito, Shigeo Fujimori, Hisashi Kashima, Masamichi Ishizaka, Hiroshi Yanagawa, Etsuko Miyamoto-Sato, Masaru Tomita
2010	J	`jnl`	Reaction graph kernels predict EC numbers of unknown enzymatic reactions in plant secondary metabolism. BMC Bioinform. Hiroto Saigo, Masahiro Hattori, Hisashi Kashima, Koji Tsuda
2009	A*	`conf`	A Linear-Time Graph Kernel. ICDM Shohei Hido, Hisashi Kashima
2009	J	`jnl`	Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation. Inf. Media Technol. Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen Bickel, Masashi Sugiyama
2009	J	`jnl`	Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation. J. Inf. Process. Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen Bickel, Masashi Sugiyama
2009	A*	`conf`	Least absolute policy iteration for robust value function approximation. ICRA Masashi Sugiyama, Hirotaka Hachiya, Hisashi Kashima, Tetsuro Morimura
2009	A	`conf`	Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction. SDM Hisashi Kashima, Tsuyoshi Kato, Yoshihiro Yamanishi, Masashi Sugiyama, Koji Tsuda
2009	B	`conf`	On Pairwise Kernels: An Efficient Alternative and Generalization Analysis. PAKDD Hisashi Kashima, Satoshi Oyama, Yoshihiro Yamanishi, Koji Tsuda
2009	J	`jnl`	Recent Advances and Trends in Large-Scale Kernel Methods. IEICE Trans. Inf. Syst. Hisashi Kashima, Tsuyoshi Idé, Tsuyoshi Kato, Masashi Sugiyama
2009	J	`jnl`	Robust Label Propagation on Multiple Networks. IEEE Trans. Neural Networks Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama
2009	J	`jnl`	Roughly balanced bagging for imbalanced data. Stat. Anal. Data Min. Shohei Hido, Hisashi Kashima, Yutaka Takahashi
2009	—	`conf`	Side Effect Prediction Using Cooperative Pathways. BIBM Mutsumi Fukuzaki, Mio Seki, Hisashi Kashima, Jun Sese
2009	J	`jnl`	Simultaneous inference of biological networks of multiple species from genome-wide data and evolutionary information: a semi-supervised approach. Bioinform. Hisashi Kashima, Yoshihiro Yamanishi, Tsuyoshi Kato, Masashi Sugiyama, Koji Tsuda
2008	B	`conf`	A new objective function for sequence labeling. ICPR Yuta Tsuboi, Hisashi Kashima
2008	A	`conf`	Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation. SDM Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen Bickel, Masashi Sugiyama
2008	A*	`conf`	Inlier-Based Outlier Detection via Direct Density Ratio Estimation. ICDM Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi Sugiyama, Takafumi Kanamori
2008	A	`conf`	Integration of Multiple Networks for Robust Label Propagation. SDM Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama
2008	B	`conf`	K-means clustering of proportional data using L1 distance. ICPR Hisashi Kashima, Jianying Hu, Bonnie K. Ray, Moninder Singh
2008	B	`conf`	Regression with interval output values. ICPR Hisashi Kashima, Kazutaka Yamasaki, Akihiro Inokuchi, Hiroto Saigo
2008	A	`conf`	Roughly Balanced Bagging for Imbalanced Data. SDM Shohei Hido, Hisashi Kashima
2008	B	`conf`	Training Conditional Random Fields Using Incomplete Annotations. COLING Yuta Tsuboi, Hisashi Kashima, Shinsuke Mori, Hiroki Oda, Yuji Matsumoto
2008	B	`conf`	Unsupervised Change Analysis Using Supervised Learning. PAKDD Shohei Hido, Tsuyoshi Idé, Hisashi Kashima, Harunobu Kubo, Hirofumi Matsuzawa
2007	J	`jnl`	A Spectrum Tree Kernel. Inf. Media Technol. Tetsuji Kuboyama, Kouichi Hirata, Hisashi Kashima, Kiyoko F. Aoki-Kinoshita, Hiroshi Yasuda
2007	—	`conf`	Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation. NIPS Masashi Sugiyama, Shinichi Nakajima, Hisashi Kashima, Paul von Bünau, Motoaki Kawanabe
2007	—	`conf`	Multi-Task Learning via Conic Programming. NIPS Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, Kiyoshi Asai
2007	J	`jnl`	Risk-Sensitive Learning via Minimization of Empirical Conditional Value-at-Risk. IEICE Trans. Inf. Syst. Hisashi Kashima
2006	A*	`conf`	A Parameterized Probabilistic Model of Network Evolution for Supervised Link Prediction. ICDM Hisashi Kashima, Naoki Abe
2006	A	`conf`	Risk-Sensitive Learning via Expected Shortfall Minimization. SDM Hisashi Kashima
2005	A*	`conf`	Network-Based Problem Detection for Distributed Systems. ICDE Hisashi Kashima, Tadashi Tsumura, Tsuyoshi Idé, Takahide Nogayama, Ryo Hirade, Hiroaki Etoh, Takeshi Fukuda
2004	—	`conf`	Effective Dimension in Anomaly Detection: Its Application to Computer Systems. JSAI Workshops Tsuyoshi Idé, Hisashi Kashima
2004	J	`jnl`	Efficient filtering methods for clustering cDNAs with spliced sequence alignment. Bioinform. Tetsuo Shibuya, Hisashi Kashima, Akihiko Konagaya
2004	A*	`conf`	Eigenspace-based anomaly detection in computer systems. KDD Tsuyoshi Idé, Hisashi Kashima
2004	A*	`conf`	Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs. ICML Hisashi Kashima, Yuta Tsuboi
2003	A*	`conf`	Marginalized Kernels Between Labeled Graphs. ICML Hisashi Kashima, Koji Tsuda, Akihiro Inokuchi
2003	A*	`conf`	Mining Significant Pairs of Patterns from Graph Structures with Class Labels. ICDM Akihiro Inokuchi, Hisashi Kashima
2002	A*	`conf`	Kernels for Semi-Structured Data. ICML Hisashi Kashima, Teruo Koyanagi