Hisashi Kashima

ORCID

Publication Activity (10 Years)

Years Active: 2002-2024
Publications (10 Years): 141

Top Venues

Publications

Xiaotian Lu, Jiyi Li, Zhen Wan, Xiaofeng Lin, Koh Takeuchi, Hisashi Kashima
Evaluating Saliency Explanations in NLP by Crowdsourcing. LREC/COLING (2024)
Xiaotian Lu, Jiyi Li, Zhen Wan, Xiaofeng Lin, Koh Takeuchi, Hisashi Kashima
Evaluating Saliency Explanations in NLP by Crowdsourcing. CoRR (2024)
Shonosuke Harada, Hisashi Kashima
InfoCEVAE: treatment effect estimation with hidden confounding variables matching. Mach. Learn. 113 (4) (2024)
Ryota Maruo, Hisashi Kashima
Efficient Preference Elicitation in Iterative Combinatorial Auctions with Many Participants. CoRR (2024)
Yuki Wakai, Koh Takeuchi, Hisashi Kashima
Recovering Population Dynamics from a Single Point Cloud Snapshot. PAKDD (3) (2024)
Guoxi Zhang, Hisashi Kashima
Learning state importance for preference-based reinforcement learning. Mach. Learn. 113 (4) (2024)
Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu, Hisashi Kashima
Treatment Effect Estimation Under Unknown Interference. PAKDD (2) (2024)
Shun Ito, Hisashi Kashima
Mitigating Cognitive Biases in Multi-Criteria Crowd Assessment. CoRR (2024)
Guoxi Zhang, Han Bao, Hisashi Kashima
Online Policy Learning from Offline Preferences. CoRR (2024)
Jill-Jênn Vie, Hisashi Kashima
Deep Knowledge Tracing is an implicit dynamic multidimensional item response theory model. CoRR (2023)
Yoichi Chikahara, Shinsaku Sakaue, Akinori Fujino, Hisashi Kashima
Making individually fair predictions with causal pathways. Data Min. Knowl. Discov. 37 (4) (2023)
Guoxi Zhang, Hisashi Kashima
Behavior Estimation from Multi-Source Data for Offline Reinforcement Learning. AAAI (2023)
Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu, Han Bao, Koh Takeuchi, Hisashi Kashima
Estimating Treatment Effects Under Heterogeneous Interference. CoRR (2023)
Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu, Han Bao, Koh Takeuchi, Hisashi Kashima
Estimating Treatment Effects Under Heterogeneous Interference. ECML/PKDD (1) (2023)
Shin'ya Yamaguchi, Daiki Chijiwa, Sekitoshi Kanai, Atsutoshi Kumagai, Hisashi Kashima
Regularizing Neural Networks with Meta-Learning Generative Models. CoRR (2023)
Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima
Mitigating Voter Attribute Bias for Fair Opinion Aggregation. AIES (2023)
Akihiro Yamaguchi, Ken Ueno, Hisashi Kashima
Time-series Shapelets with Learnable Lengths. CIKM (2023)
Ryu Shirakami, Toshiya Kitahara, Koh Takeuchi, Hisashi Kashima
QTNet: Theory-based Queue Length Prediction for Urban Traffic. KDD (2023)
Kosuke Yoshimura, Hisashi Kashima
Label Selection Approach to Learning from Crowds. ICONIP (8) (2023)
Xiaotian Lu, Jiyi Li, Koh Takeuchi, Hisashi Kashima
Multiview Representation Learning from Crowdsourced Triplet Comparisons. CoRR (2023)
Kosuke Yoshimura, Hisashi Kashima
Label Selection Approach to Learning from Crowds. CoRR (2023)
Shin'ya Yamaguchi, Daiki Chijiwa, Sekitoshi Kanai, Atsutoshi Kumagai, Hisashi Kashima
Regularizing Neural Networks with Meta-Learning Generative Models. NeurIPS (2023)
Xiaotian Lu, Jiyi Li, Koh Takeuchi, Hisashi Kashima
Multiview Representation Learning from Crowdsourced Triplet Comparisons. WWW (2023)
Koh Takeuchi, Ryo Nishida, Hisashi Kashima, Masaki Onishi
Causal Effect Estimation on Hierarchical Spatial Graph Data. KDD (2023)
Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima
Mitigating Observation Biases in Crowdsourced Label Aggregation. CoRR (2023)
Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima
Mitigating Voter Attribute Bias for Fair Opinion Aggregation. CoRR (2023)
Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Sekitoshi Kanai, Masanori Yamada, Yuki Yamanaka, Hisashi Kashima
Learning Optimal Priors for Task-Invariant Representations in Variational Autoencoders. KDD (2022)
Yoichi Chikahara, Makoto Yamada, Hisashi Kashima
Feature selection for discovering distributional treatment effect modifiers. UAI (2022)
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Twin Papers: A Simple Framework of Causal Inference for Citations via Coupling. CIKM (2022)
Shin'ya Yamaguchi, Sekitoshi Kanai, Atsutoshi Kumagai, Daiki Chijiwa, Hisashi Kashima
Transfer Learning with Pre-trained Conditional Generative Models. CoRR (2022)
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Poincare: Recommending Publication Venues via Treatment Effect Estimation. J. Informetrics 16 (2) (2022)
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Twin Papers: A Simple Framework of Causal Inference for Citations via Coupling. CoRR (2022)
Shogo Hayashi, Junya Honda, Hisashi Kashima
Bayesian optimization with partially specified queries. Mach. Learn. 111 (3) (2022)
Yoichi Chikahara, Makoto Yamada, Hisashi Kashima
Feature Selection for Discovering Distributional Treatment Effect Modifiers. CoRR (2022)
Hisashi Kashima, Satoshi Oyama, Hiromi Arai, Junichiro Mori
Trustworthy Human Computation: A Survey. CoRR (2022)
Maya Okawa, Tomoharu Iwata, Yusuke Tanaka, Takeshi Kurashima, Hiroyuki Toda, Hisashi Kashima
Context-aware spatio-temporal event prediction via convolutional Hawkes processes. Mach. Learn. 111 (8) (2022)
Akira Tanimoto, So Yamada, Takashi Takenouchi, Masashi Sugiyama, Hisashi Kashima
Improving imbalanced classification using near-miss instances. Expert Syst. Appl. 201 (2022)
Guoxi Zhang, Hisashi Kashima
Behavior Estimation from Multi-Source Data for Offline Reinforcement Learning. CoRR (2022)
Akihiro Yamaguchi, Ken Ueo, Hisashi Kashima
Learning Evolvable Time-series Shapelets. ICDE (2022)
Jill-Jênn Vie, Tomas Rigaux, Hisashi Kashima
Variational Factorization Machines for Preference Elicitation in Large-Scale Recommender Systems. Big Data (2022)
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Constant Time Graph Neural Networks. ACM Trans. Knowl. Discov. Data 16 (5) (2022)
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Re-evaluating Word Mover's Distance. ICML (2022)
Guoxi Zhang, Hisashi Kashima
Batch Reinforcement Learning from Crowds. ECML/PKDD (4) (2022)
Akihiro Yamaguchi, Ken Ueno, Hisashi Kashima
Learning Time-series Shapelets Enhancing Discriminability. SDM (2022)
Guoxi Zhang, Jiyi Li, Hisashi Kashima
Improving Pairwise Rank Aggregation via Querying for Rank Difference. DSAA (2022)
Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima
Mitigating Observation Biases in Crowdsourced Label Aggregation. ICPR (2022)
Sein Minn, Jill-Jênn Vie, Koh Takeuchi, Hisashi Kashima, Feida Zhu
Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations. AAAI (2022)
Jill-Jênn Vie, Tomas Rigaux, Hisashi Kashima
Variational Factorization Machines for Preference Elicitation in Large-Scale Recommender Systems. CoRR (2022)
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Random Features Strengthen Graph Neural Networks. SDM (2021)
Jiuding Duan, Hisashi Kashima
Learning to Rank for Multi-Step Ahead Time-Series Forecasting. IEEE Access 9 (2021)
Maya Okawa, Tomoharu Iwata, Yusuke Tanaka, Hiroyuki Toda, Takeshi Kurashima, Hisashi Kashima
Dynamic Hawkes Processes for Discovering Time-evolving Communities' States behind Diffusion Processes. CoRR (2021)
Shonosuke Harada, Hisashi Kashima
GraphITE: Estimating Individual Effects of Graph-structured Treatments. CIKM (2021)
Xiaotian Lu, Arseny Tolmachev, Tatsuya Yamamoto, Koh Takeuchi, Seiji Okajima, Tomoyoshi Takebayashi, Koji Maruhashi, Hisashi Kashima
Crowdsourcing Evaluation of Saliency-Based XAI Methods. ECML/PKDD (5) (2021)
Luu Huu Phuc, Koh Takeuchi, Seiji Okajima, Arseny Tolmachev, Tomoyoshi Takebayashi, Koji Maruhashi, Hisashi Kashima
Inter-domain Multi-relational Link Prediction. CoRR (2021)
Yoichi Chikahara, Shinsaku Sakaue, Akinori Fujino, Hisashi Kashima
Learning Individually Fair Classifier with Path-Specific Causal-Effect Constraint. AISTATS (2021)
Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima
Regret Minimization for Causal Inference on Large Treatment Space. AISTATS (2021)
Luu Huu Phuc, Koh Takeuchi, Seiji Okajima, Arseny Tolmachev, Tomoyoshi Takebayashi, Koji Maruhashi, Hisashi Kashima
Inter-domain Multi-relational Link Prediction. ECML/PKDD (2) (2021)
Guoxi Zhang, Hisashi Kashima
Batch Reinforcement Learning from Crowds. CoRR (2021)
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. ITSC (2021)
Jiyi Li, Lucas Ryo Endo, Hisashi Kashima
Label Aggregation for Crowdsourced Triplet Similarity Comparisons. ICONIP (6) (2021)
Koh Takeuchi, Ryo Nishida, Hisashi Kashima, Masaki Onishi
Grab the Reins of Crowds: Estimating the Effects of Crowd Movement Guidance Using Causal Inference. AAMAS (2021)
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Re-evaluating Word Mover's Distance. CoRR (2021)
Sein Minn, Jill-Jênn Vie, Koh Takeuchi, Hisashi Kashima, Feida Zhu
Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations. CoRR (2021)
Maya Okawa, Tomoharu Iwata, Yusuke Tanaka, Hiroyuki Toda, Takeshi Kurashima, Hisashi Kashima
Dynamic Hawkes Processes for Discovering Time-evolving Communities' States behind Diffusion Processes. KDD (2021)
Ayato Toyokuni, Sho Yokoi, Hisashi Kashima, Makoto Yamada
Computationally Efficient Wasserstein Loss for Structured Labels. CoRR (2021)
Toshihiro Kamishima, Shotaro Akaho, Yukino Baba, Hisashi Kashima
Preliminary Experiments to Examine the Stability of Bias-Aware Techniques. BIAS (2021)
Xiaotian Lu, Arseny Tolmachev, Tatsuya Yamamoto, Koh Takeuchi, Seiji Okajima, Tomoyoshi Takebayashi, Koji Maruhashi, Hisashi Kashima
Crowdsourcing Evaluation of Saliency-based XAI Methods. CoRR (2021)
Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima
Causal Combinatorial Factorization Machines for Set-Wise Recommendation. PAKDD (2) (2021)
Ayato Toyokuni, Sho Yokoi, Hisashi Kashima, Makoto Yamada
Computationally Efficient Wasserstein Loss for Structured Labels. EACL (Student Research Workshop) (2021)
Ryoma Sato, Marco Cuturi, Makoto Yamada, Hisashi Kashima
Fast and Robust Comparison of Probability Measures in Heterogeneous Spaces. CoRR (2020)
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Random Features Strengthen Graph Neural Networks. CoRR (2020)
Yukino Baba, Jiyi Li, Hisashi Kashima
CrowDEA: Multi-View Idea Prioritization with Crowds. HCOMP (2020)
Shun Ito, Yukino Baba, Tetsu Isomura, Hisashi Kashima
Synthetic accessibility assessment using auxiliary responses. Expert Syst. Appl. 145 (2020)
Shonosuke Harada, Hisashi Kashima
Counterfactual Propagation for Semi-supervised Individual Treatment Effect Estimation. ECML/PKDD (1) (2020)
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Poincare: Recommending Publication Venues via Treatment Effect Estimation. CoRR (2020)
Tatsuya Shiraishi, Tam Le, Hisashi Kashima, Makoto Yamada
Topological Bayesian Optimization with Persistence Diagrams. ECAI (2020)
Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima
Regret Minimization for Causal Inference on Large Treatment Space. CoRR (2020)
Jiyi Li, Yasushi Kawase, Yukino Baba, Hisashi Kashima
Performance as a Constraint: An Improved Wisdom of Crowds Using Performance Regularization. IJCAI (2020)
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Fast Unbalanced Optimal Transport on Tree. CoRR (2020)
Yukino Baba, Jiyi Li, Hisashi Kashima
CrowDEA: Multi-view Idea Prioritization with Crowds. CoRR (2020)
Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki, Yukino Baba, Ichigaku Takigawa, Yoshihiro Yamanishi, Hisashi Kashima
Dual graph convolutional neural network for predicting chemical networks. BMC Bioinform. (3) (2020)
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Fast Unbalanced Optimal Transport on a Tree. NeurIPS (2020)
Yang Liu, Hisashi Kashima
Chemical Property Prediction Under Experimental Biases. CoRR (2020)
Hitoshi Kusano, Yuji Horiguchi, Yukino Baba, Hisashi Kashima
Stress Prediction from Head Motion. DSAA (2020)
Luu Huu Phuc, Koh Takeuchi, Makoto Yamada, Hisashi Kashima
Simultaneous Link Prediction on Unaligned Networks Using Graph Embedding and Optimal Transport. DSAA (2020)
Shonosuke Harada, Hisashi Kashima
GraphITE: Estimating Individual Effects of Graph-structured Treatments. CoRR (2020)
Yasutoshi Ida, Sekitoshi Kanai, Yasuhiro Fujiwara, Tomoharu Iwata, Koh Takeuchi, Hisashi Kashima
Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance. ICML (2020)
Shonosuke Harada, Hisashi Kashima
Counterfactual Propagation for Semi-Supervised Individual Treatment Effect Estimation. CoRR (2020)
Yan Gu, Jiuding Duan, Hisashi Kashima
An Intransitivity Model for Matchup and Pairwise Comparison. ICPR (2020)
Kosuke Yoshimura, Tomoaki Iwase, Yukino Baba, Hisashi Kashima
Interdependence Model for Multi-label Classification. ICANN (4) (2019)
Yusuke Sakata, Yukino Baba, Hisashi Kashima
Crownn: Human-in-the-loop Network with Crowd-generated Inputs. ICASSP (2019)
Takeru Sunahase, Yukino Baba, Hisashi Kashima
Probabilistic Modeling of Peer Correction and Peer Assessment. EDM (2019)
Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric Gouy-Pailler, Jamal Atif
Theoretical evidence for adversarial robustness through randomization: the case of the Exponential family. CoRR (2019)
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Approximation Ratios of Graph Neural Networks for Combinatorial Problems. CoRR (2019)
Shogo Hayashi, Yoshinobu Kawahara, Hisashi Kashima
Active Change-Point Detection. ACML (2019)
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Approximation Ratios of Graph Neural Networks for Combinatorial Problems. NeurIPS (2019)
Shogo Hayashi, Akira Tanimoto, Hisashi Kashima
Long-Term Prediction of Small Time-Series Data Using Generalized Distillation. IJCNN (2019)
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Constant Time Graph Neural Networks. CoRR (2019)
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Learning to Sample Hard Instances for Graph Algorithms. ACML (2019)
Ryoma Sato, Makoto Yamada, Hisashi Kashima
Learning to Find Hard Instances of Graph Problems. CoRR (2019)

Hisashi Kashima.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Hisashi Kashima