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Journal Articles
- 2024
[j40]Hisashi Kashima, Satoshi Oyama, Hiromi Arai, Junichiro Mori:
Trustworthy human computation: a survey. Artif. Intell. Rev. 57(12): 322 (2024)- [j39]Shonosuke Harada, Hisashi Kashima:
InfoCEVAE: treatment effect estimation with hidden confounding variables matching. Mach. Learn. 113(4): 1799-1817 (2024) - [j38]Guoxi Zhang
, Hisashi Kashima:
Learning state importance for preference-based reinforcement learning. Mach. Learn. 113(4): 1885-1901 (2024) - 2023
- [j37]Yoichi Chikahara, Shinsaku Sakaue, Akinori Fujino, Hisashi Kashima:
Making individually fair predictions with causal pathways. Data Min. Knowl. Discov. 37(4): 1327-1373 (2023) - 2022
- [j36]Akira Tanimoto, So Yamada, Takashi Takenouchi, Masashi Sugiyama, Hisashi Kashima:
Improving imbalanced classification using near-miss instances. Expert Syst. Appl. 201: 117130 (2022) - [j35]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Poincare: Recommending Publication Venues via Treatment Effect Estimation. J. Informetrics 16(2): 101283 (2022) - [j34]Shogo Hayashi, Junya Honda, Hisashi Kashima:
Bayesian optimization with partially specified queries. Mach. Learn. 111(3): 1019-1048 (2022) - [j33]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): 2929-2950 (2022) - [j32]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Constant Time Graph Neural Networks. ACM Trans. Knowl. Discov. Data 16(5): 92:1-92:31 (2022) - 2021
- [j31]Jiuding Duan, Hisashi Kashima:
Learning to Rank for Multi-Step Ahead Time-Series Forecasting. IEEE Access 9: 49372-49386 (2021) - 2020
- [j30]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. 21-S(3): 94 (2020) - [j29]Shun Ito, Yukino Baba, Tetsu Isomura, Hisashi Kashima:
Synthetic accessibility assessment using auxiliary responses. Expert Syst. Appl. 145: 113106 (2020) - 2018
- [j28]Takuya Kuwahara, Yukino Baba, Hisashi Kashima, Takeshi Kishikawa, Jun'ichi Tsurumi, Tomoyuki Haga, Yoshihiro Ujiie, Takamitsu Sasaki, Hideki Matsushima:
Supervised and Unsupervised Intrusion Detection Based on CAN Message Frequencies for In-vehicle Network. J. Inf. Process. 26: 306-313 (2018) - 2017
- [j27]Sho Yokoi, Hiroshi Kajino, Hisashi Kashima:
Link Prediction in Sparse Networks by Incidence Matrix Factorization. J. Inf. Process. 25: 477-485 (2017) - 2016
- [j26]Naoki Otani, Yukino Baba, Hisashi Kashima:
Quality control of crowdsourced classification using hierarchical class structures. Expert Syst. Appl. 58: 155-163 (2016) - [j25]Yukino Baba, Kei Kinoshita, Hisashi Kashima:
Participation recommendation system for crowdsourcing contests. Expert Syst. Appl. 58: 174-183 (2016) - [j24]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. Int. J. Data Sci. Anal. 2(1-2): 45-60 (2016) - 2014
- [j23]Hiroshi Kajino, Hiromi Arai, Hisashi Kashima:
Preserving worker privacy in crowdsourcing. Data Min. Knowl. Discov. 28(5-6): 1314-1335 (2014) - [j22]Yukino Baba, Hisashi Kashima, Kei Kinoshita, Goushi Yamaguchi, Yosuke Akiyoshi:
Leveraging non-expert crowdsourcing workers for improper task detection in crowdsourcing marketplaces. Expert Syst. Appl. 41(6): 2678-2687 (2014) - 2013
- [j21]Hiroto Saigo, Hisashi Kashima, Koji Tsuda:
Fast Iterative Mining Using Sparsity-Inducing Loss Functions. IEICE Trans. Inf. Syst. 96-D(8): 1766-1773 (2013) - [j20]Xu Sun, Hisashi Kashima, Naonori Ueda:
Large-Scale Personalized Human Activity Recognition Using Online Multitask Learning. IEEE Trans. Knowl. Data Eng. 25(11): 2551-2563 (2013) - 2012
- [j19]Atsuhiro Narita, Kohei Hayashi, Ryota Tomioka, Hisashi Kashima:
Tensor factorization using auxiliary information. Data Min. Knowl. Discov. 25(2): 298-324 (2012) - [j18]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) - [j17]Satoshi Oyama, Kohei Hayashi, Hisashi Kashima:
Link Prediction Across Time via Cross-Temporal Locality Preserving Projections. IEICE Trans. Inf. Syst. 95-D(11): 2664-2673 (2012) - 2011
- [j16]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) - 2010
- [j15]Hiroto Saigo, Masahiro Hattori, Hisashi Kashima, Koji Tsuda:
Reaction graph kernels predict EC numbers of unknown enzymatic reactions in plant secondary metabolism. BMC Bioinform. 11(S-1): 31 (2010) - [j14]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 Bioinform. 11: 350 (2010) - [j13]Masashi Sugiyama, Hirotaka Hachiya, Hisashi Kashima, Tetsuro Morimura:
Least Absolute Policy Iteration-A Robust Approach to Value Function Approximation. IEICE Trans. Inf. Syst. 93-D(9): 2555-2565 (2010) - [j12]Hisashi Kashima, Satoshi Oyama, Yoshihiro Yamanishi, Koji Tsuda:
Cartesian Kernel: An Efficient Alternative to the Pairwise Kernel. IEICE Trans. Inf. Syst. 93-D(10): 2672-2679 (2010) - [j11]Tsuyoshi Kato, Kinya Okada, Hisashi Kashima, Masashi Sugiyama:
A Transfer Learning Approach and Selective Integration of Multiple Types of Assays for Biological Network Inference. Int. J. Knowl. Discov. Bioinform. 1(1): 66-80 (2010) - [j10]Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, Kiyoshi Asai:
Conic Programming for Multitask Learning. IEEE Trans. Knowl. Data Eng. 22(7): 957-968 (2010) - 2009
- [j9]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. Bioinform. 25(22): 2962-2968 (2009) - [j8]Hisashi Kashima, Tsuyoshi Idé, Tsuyoshi Kato, Masashi Sugiyama:
Recent Advances and Trends in Large-Scale Kernel Methods. IEICE Trans. Inf. Syst. 92-D(7): 1338-1353 (2009) - [j7]Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen Bickel, Masashi Sugiyama:
Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation. Inf. Media Technol. 4(2): 529-546 (2009) - [j6]Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen Bickel, Masashi Sugiyama:
Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation. J. Inf. Process. 17: 138-155 (2009) - [j5]Shohei Hido, Hisashi Kashima, Yutaka Takahashi:
Roughly balanced bagging for imbalanced data. Stat. Anal. Data Min. 2(5-6): 412-426 (2009) - [j4]Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama:
Robust Label Propagation on Multiple Networks. IEEE Trans. Neural Networks 20(1): 35-44 (2009) - 2007
- [j3]Hisashi Kashima:
Risk-Sensitive Learning via Minimization of Empirical Conditional Value-at-Risk. IEICE Trans. Inf. Syst. 90-D(12): 2043-2052 (2007) - [j2]Tetsuji Kuboyama, Kouichi Hirata, Hisashi Kashima, Kiyoko F. Aoki-Kinoshita, Hiroshi Yasuda:
A Spectrum Tree Kernel. Inf. Media Technol. 2(1): 292-299 (2007) - 2004
- [j1]Tetsuo Shibuya, Hisashi Kashima, Akihiko Konagaya:
Efficient filtering methods for clustering cDNAs with spliced sequence alignment. Bioinform. 20(1): 29-39 (2004)
Conference and Workshop Papers
- 2024
- [c154]Xiaotian Lu, Jiyi Li, Zhen Wan, Xiaofeng Lin, Koh Takeuchi, Hisashi Kashima:
Evaluating Saliency Explanations in NLP by Crowdsourcing. LREC/COLING 2024: 6431-6443 - [c153]Yu Mitsuzumi, Akisato Kimura, Hisashi Kashima:
Understanding and Improving Source-Free Domain Adaptation from a Theoretical Perspective. CVPR 2024: 28515-28524 - [c152]Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu, Hisashi Kashima:
Treatment Effect Estimation Under Unknown Interference. PAKDD (2) 2024: 28-42 - [c151]Yuki Wakai, Koh Takeuchi, Hisashi Kashima:
Recovering Population Dynamics from a Single Point Cloud Snapshot. PAKDD (3) 2024: 302-315 - 2023
- [c150]Guoxi Zhang, Hisashi Kashima:
Behavior Estimation from Multi-Source Data for Offline Reinforcement Learning. AAAI 2023: 11201-11209 - [c149]Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima:
Mitigating Voter Attribute Bias for Fair Opinion Aggregation. AIES 2023: 170-180 - [c148]Akihiro Yamaguchi, Ken Ueno, Hisashi Kashima:
Time-series Shapelets with Learnable Lengths. CIKM 2023: 2866-2876 - [c147]Kosuke Yoshimura, Hisashi Kashima:
Label Selection Approach to Learning from Crowds. ICONIP (8) 2023: 207-221 - [c146]Koh Takeuchi, Ryo Nishida, Hisashi Kashima, Masaki Onishi:
Causal Effect Estimation on Hierarchical Spatial Graph Data. KDD 2023: 2145-2154 - [c145]Ryu Shirakami, Toshiya Kitahara, Koh Takeuchi, Hisashi Kashima:
QTNet: Theory-based Queue Length Prediction for Urban Traffic. KDD 2023: 4832-4841 - [c144]Shin'ya Yamaguchi, Daiki Chijiwa, Sekitoshi Kanai, Atsutoshi Kumagai, Hisashi Kashima:
Regularizing Neural Networks with Meta-Learning Generative Models. NeurIPS 2023 - [c143]Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu, Han Bao, Koh Takeuchi, Hisashi Kashima:
Estimating Treatment Effects Under Heterogeneous Interference. ECML/PKDD (1) 2023: 576-592 - [c142]Xiaotian Lu, Jiyi Li, Koh Takeuchi, Hisashi Kashima:
Multiview Representation Learning from Crowdsourced Triplet Comparisons. WWW 2023: 3827-3836 - 2022
- [c141]Sein Minn, Jill-Jênn Vie, Koh Takeuchi, Hisashi Kashima, Feida Zhu:
Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations. AAAI 2022: 12810-12818 - [c140]Jill-Jênn Vie, Tomas Rigaux, Hisashi Kashima:
Variational Factorization Machines for Preference Elicitation in Large-Scale Recommender Systems. IEEE Big Data 2022: 5607-5614 - [c139]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Twin Papers: A Simple Framework of Causal Inference for Citations via Coupling. CIKM 2022: 4444-4448 - [c138]Guoxi Zhang, Jiyi Li, Hisashi Kashima:
Improving Pairwise Rank Aggregation via Querying for Rank Difference. DSAA 2022: 1-9 - [c137]Akihiro Yamaguchi, Ken Ueno, Hisashi Kashima:
Learning Evolvable Time-series Shapelets. ICDE 2022: 793-805 - [c136]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Re-evaluating Word Mover's Distance. ICML 2022: 19231-19249 - [c135]Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima:
Mitigating Observation Biases in Crowdsourced Label Aggregation. ICPR 2022: 1171-1177 - [c134]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: 1739-1748 - [c133]Guoxi Zhang, Hisashi Kashima:
Batch Reinforcement Learning from Crowds. ECML/PKDD (4) 2022: 38-51 - [c132]Akihiro Yamaguchi, Ken Ueno, Hisashi Kashima:
Learning Time-series Shapelets Enhancing Discriminability. SDM 2022: 190-198 - [c131]Yoichi Chikahara, Makoto Yamada, Hisashi Kashima:
Feature selection for discovering distributional treatment effect modifiers. UAI 2022: 400-410 - 2021
- [c130]Yoichi Chikahara, Shinsaku Sakaue, Akinori Fujino, Hisashi Kashima:
Learning Individually Fair Classifier with Path-Specific Causal-Effect Constraint. AISTATS 2021: 145-153 - [c129]Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima:
Regret Minimization for Causal Inference on Large Treatment Space. AISTATS 2021: 946-954 - [c128]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: 1290-1298 - [c127]Toshihiro Kamishima, Shotaro Akaho, Yukino Baba, Hisashi Kashima:
Preliminary Experiments to Examine the Stability of Bias-Aware Techniques. BIAS 2021: 25-35 - [c126]Shonosuke Harada, Hisashi Kashima:
GraphITE: Estimating Individual Effects of Graph-structured Treatments. CIKM 2021: 659-668 - [c125]Ayato Toyokuni, Sho Yokoi, Hisashi Kashima, Makoto Yamada:
Computationally Efficient Wasserstein Loss for Structured Labels. EACL (Student Research Workshop) 2021: 1-7 - [c124]Jiyi Li, Lucas Ryo Endo, Hisashi Kashima:
Label Aggregation for Crowdsourced Triplet Similarity Comparisons. ICONIP (6) 2021: 176-185 - [c123]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: 1286-1291 - [c122]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: 1276-1286 - [c121]Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima:
Causal Combinatorial Factorization Machines for Set-Wise Recommendation. PAKDD (2) 2021: 498-509 - [c120]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: 285-301 - [c119]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: 431-446 - [c118]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Random Features Strengthen Graph Neural Networks. SDM 2021: 333-341 - 2020
- [c117]Luu Huu Phuc, Koh Takeuchi, Makoto Yamada, Hisashi Kashima:
Simultaneous Link Prediction on Unaligned Networks Using Graph Embedding and Optimal Transport. DSAA 2020: 245-254 - [c116]Hitoshi Kusano, Yuji Horiguchi, Yukino Baba, Hisashi Kashima:
Stress Prediction from Head Motion. DSAA 2020: 488-495 - [c115]Tatsuya Shiraishi, Tam Le, Hisashi Kashima, Makoto Yamada:
Topological Bayesian Optimization with Persistence Diagrams. ECAI 2020: 1483-1490 - [c114]Yukino Baba, Jiyi Li, Hisashi Kashima:
CrowDEA: Multi-View Idea Prioritization with Crowds. HCOMP 2020: 23-32 - [c113]Yasutoshi Ida, Sekitoshi Kanai, Yasuhiro Fujiwara, Tomoharu Iwata, Koh Takeuchi, Hisashi Kashima:
Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance. ICML 2020: 4594-4603 - [c112]Yan Gu, Jiuding Duan, Hisashi Kashima:
An Intransitivity Model for Matchup and Pairwise Comparison. ICPR 2020: 692-698 - [c111]Jiyi Li, Yasushi Kawase, Yukino Baba, Hisashi Kashima:
Performance as a Constraint: An Improved Wisdom of Crowds Using Performance Regularization. IJCAI 2020: 1534-1541 - [c110]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Fast Unbalanced Optimal Transport on a Tree. NeurIPS 2020 - [c109]Shonosuke Harada, Hisashi Kashima:
Counterfactual Propagation for Semi-supervised Individual Treatment Effect Estimation. ECML/PKDD (1) 2020: 542-558 - 2019
- [c108]Jill-Jênn Vie, Hisashi Kashima:
Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing. AAAI 2019: 750-757 - [c107]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Learning to Sample Hard Instances for Graph Algorithms. ACML 2019: 503-518 - [c106]Shogo Hayashi, Yoshinobu Kawahara, Hisashi Kashima:
Active Change-Point Detection. ACML 2019: 1017-1032 - [c105]Takeru Sunahase, Yukino Baba, Hisashi Kashima:
Probabilistic Modeling of Peer Correction and Peer Assessment. EDM 2019 - [c104]Kosuke Yoshimura, Tomoaki Iwase, Yukino Baba, Hisashi Kashima:
Interdependence Model for Multi-label Classification. ICANN (4) 2019: 55-68 - [c103]Yusuke Sakata, Yukino Baba, Hisashi Kashima:
Crownn: Human-in-the-loop Network with Crowd-generated Inputs. ICASSP 2019: 7555-7559 - [c102]Shogo Hayashi, Akira Tanimoto, Hisashi Kashima:
Long-Term Prediction of Small Time-Series Data Using Generalized Distillation. IJCNN 2019: 1-8 - [c101]Daiki Tanaka, Makoto Yamada, Hisashi Kashima, Takeshi Kishikawa, Tomoyuki Haga, Takamitsu Sasaki:
In-Vehicle Network Intrusion Detection and Explanation Using Density Ratio Estimation. ITSC 2019: 2238-2243 - [c100]Yasutoshi Ida, Yasuhiro Fujiwara, Hisashi Kashima:
Fast Sparse Group Lasso. NeurIPS 2019: 1700-1708 - [c99]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Approximation Ratios of Graph Neural Networks for Combinatorial Problems. NeurIPS 2019: 4083-4092 - [c98]Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric Gouy-Pailler, Jamal Atif:
Theoretical evidence for adversarial robustness through randomization. NeurIPS 2019: 11838-11848 - [c97]Shonosuke Harada, Kazuki Taniguchi, Makoto Yamada, Hisashi Kashima:
Context-Regularized Neural Collaborative Filtering for Game App Recommendation. RecSys (Late-Breaking Results) 2019: 16-20 - [c96]Daiki Tanaka, Yukino Baba, Hisashi Kashima, Yuta Okubo:
Large-scale Driver Identification Using Automobile Driving Data. SMC 2019: 3441-3446 - 2018
- [c95]Ryusuke Takahama, Yukino Baba, Nobuyuki Shimizu, Sumio Fujita, Hisashi Kashima:
AdaFlock: Adaptive Feature Discovery for Human-in-the-loop Predictive Modeling. AAAI 2018: 1619-1626 - [c94]Yukino Baba, Tomoumi Takase, Kyohei Atarashi, Satoshi Oyama, Hisashi Kashima:
Data Analysis Competition Platform for Educational Purposes: Lessons Learned and Future Challenges. AAAI 2018: 7887-7892 - [c93]Junpei Naito, Yukino Baba, Hisashi Kashima, Takenori Takaki, Takuya Funo:
Predictive Modeling of Learning Continuation in Preschool Education Using Temporal Patterns of Development Tests. AAAI 2018: 7934-7940 - [c92]Ryoma Sato, Hisashi Kashima, Takehiro Yamamoto:
Short-Term Precipitation Prediction with Skip-Connected PredNet. ICANN (3) 2018: 373-382 - [c91]Jiyi Li, Yukino Baba, Hisashi Kashima:
Incorporating Worker Similarity for Label Aggregation in Crowdsourcing. ICANN (2) 2018: 596-606 - [c90]Hirotaka Akita, Kosuke Nakago, Tomoki Komatsu, Yohei Sugawara, Shin-ichi Maeda, Yukino Baba, Hisashi Kashima:
BayesGrad: Explaining Predictions of Graph Convolutional Networks. ICONIP (5) 2018: 81-92 - [c89]Jiyi Li, Yukino Baba, Hisashi Kashima:
Simultaneous Clustering and Ranking from Pairwise Comparisons. IJCAI 2018: 1554-1560 - [c88]Guoxi Zhang, Tomoharu Iwata, Hisashi Kashima:
On Reducing Dimensionality of Labeled Data Efficiently. PAKDD (3) 2018: 77-88 - [c87]Takuya Kuwahara, Yukino Baba, Hisashi Kashima, Takeshi Kishikawa, Jun'ichi Tsurumi, Tomoyuki Haga, Yoshihiro Ujiie, Takamitsu Sasaki, Hideki Matsushima:
Payload-Based Statistical Intrusion Detection for In-Vehicle Networks. PAKDD (Workshops) 2018: 186-192 - 2017
- [c86]Takeru Sunahase, Yukino Baba, Hisashi Kashima:
Pairwise HITS: Quality Estimation from Pairwise Comparisons in Creator-Evaluator Crowdsourcing Process. AAAI 2017: 977-984 - [c85]Nozomi Nori, Hisashi Kashima, Kazuto Yamashita, Susumu Kunisawa, Yuichi Imanaka:
Learning Implicit Tasks for Patient-Specific Risk Modeling in ICU. AAAI 2017: 1481-1487 - [c84]Yuji Horiguchi, Yukino Baba, Hisashi Kashima, Masahito Suzuki, Hiroki Kayahara, Jun Maeno:
Predicting Fuel Consumption and Flight Delays for Low-Cost Airlines. AAAI 2017: 4686-4693 - [c83]Jiyi Li, Yukino Baba, Hisashi Kashima:
Hyper Questions: Unsupervised Targeting of a Few Experts in Crowdsourcing. CIKM 2017: 1069-1078 - [c82]Jill-Jênn Vie, Florian Yger, Ryan Lahfa, Basile Clement, Kévin Cocchi, Thomas Chalumeau, Hisashi Kashima:
Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario. MANPU@ICDAR 2017: 21-26 - [c81]Koh Takeuchi, Hisashi Kashima, Naonori Ueda:
Autoregressive Tensor Factorization for Spatio-Temporal Predictions. ICDM 2017: 1105-1110 - [c80]Kosuke Yoshimura, Yukino Baba, Hisashi Kashima:
Quality Control for Crowdsourced Multi-label Classification Using RAkEL. ICONIP (1) 2017: 64-73 - [c79]Hirotaka Akita, Yukino Baba, Hisashi Kashima, Atsuto Seko:
Atomic Distance Kernel for Material Property Prediction. ICONIP (1) 2017: 526-533 - [c78]Jiuding Duan, Jiyi Li, Yukino Baba, Hisashi Kashima:
A Generalized Model for Multidimensional Intransitivity. PAKDD (2) 2017: 840-852 - [c77]Guoxi Zhang, Tomoharu Iwata, Hisashi Kashima:
Robust Multi-view Topic Modeling by Incorporating Detecting Anomalies. ECML/PKDD (2) 2017: 238-250 - [c76]Jiyi Li, Tomohiro Arai, Yukino Baba, Hisashi Kashima, Shotaro Miwa:
Distributed Multi-task Learning for Sensor Network. ECML/PKDD (2) 2017: 657-672 - [c75]Jiyi Li, Hisashi Kashima:
Iterative Reduction Worker Filtering for Crowdsourced Label Aggregation. WISE (2) 2017: 46-54 - 2016
- [c74]Sho Yokoi, Hiroshi Kajino, Hisashi Kashima:
Link Prediction by Incidence Matrix Factorization. ECAI 2016: 1730-1731 - [c73]Patrick Jörger, Yukino Baba, Hisashi Kashima:
Learning to Enumerate. ICANN (1) 2016: 453-460 - [c72]Ryusuke Takahama, Toshihiro Kamishima, Hisashi Kashima:
Progressive Comparison for Ranking Estimation. IJCAI 2016: 3882-3888 - [c71]Kaito Fujii, Hisashi Kashima:
Budgeted stream-based active learning via adaptive submodular maximization. NIPS 2016: 514-522 - 2015
- [c70]Junpei Komiyama, Junya Honda, Hisashi Kashima, Hiroshi Nakagawa:
Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem. COLT 2015: 1141-1154 - [c69]Satoshi Oyama, Yukino Baba, Ikki Ohmukai, Hiroaki Dokoshi, Hisashi Kashima:
From one star to three stars: Upgrading legacy open data using crowdsourcing. DSAA 2015: 1-9 - [c68]Naoki Otani, Yukino Baba, Hisashi Kashima:
Quality Control for Crowdsourced Hierarchical Classification. ICDM 2015: 937-942 - [c67]Nozomi Nori, Hisashi Kashima, Kazuto Yamashita, Hiroshi Ikai, Yuichi Imanaka:
Simultaneous Modeling of Multiple Diseases for Mortality Prediction in Acute Hospital Care. KDD 2015: 855-864 - [c66]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:
Predictive Approaches for Low-Cost Preventive Medicine Program in Developing Countries. KDD 2015: 1681-1690 - [c65]Shunsuke Kajimura, Yukino Baba, Hiroshi Kajino, Hisashi Kashima:
Quality Control for Crowdsourced POI Collection. PAKDD (2) 2015: 255-267 - [c64]Jiuding Duan, Atsuto Seko, Hisashi Kashima:
Quantum Energy Prediction Using Graph Kernel. SMC 2015: 1651-1656 - 2014
- [c63]Yukino Baba, Nozomi Nori, Shigeru Saito, Hisashi Kashima:
Crowdsourced data analytics: A case study of a predictive modeling competition. DSAA 2014: 284-289 - [c62]Yukino Baba, Nozomi Nori, Shigeru Saito, Hisashi Kashima:
Crowdsourced Data Analytics: A Case Study of a Predictive Modeling Competition. HCOMP 2014: 4-5 - [c61]Shunsuke Kajimura, Yukino Baba, Hiroshi Kajino, Hisashi Kashima:
Quality Control for Crowdsourced Enumeration Tasks. HCOMP 2014: 28-29 - [c60]Hiroshi Kajino, Yukino Baba, Hisashi Kashima:
Instance-Privacy Preserving Crowdsourcing. HCOMP 2014: 96-103 - [c59]Ryoma Kawajiri, Masamichi Shimosaka, Hisashi Kashima:
Steered crowdsensing: incentive design towards quality-oriented place-centric crowdsensing. UbiComp 2014: 691-701 - [c58]Issei Sato, Hisashi Kashima, Hiroshi Nakagawa:
Latent Confusion Analysis by Normalized Gamma Construction. ICML 2014: 1116-1124 - [c57]Toshihiro Watanabe, Hisashi Kashima:
A Label Completion Approach to Crowd Approximation. ICONIP (2) 2014: 377-385 - [c56]Jingjing Wang, Satoshi Oyama, Masahito Kurihara, Hisashi Kashima:
Learning an accurate entity resolution model from crowdsourced labels. ICUIMC 2014: 103:1-103:8 - [c55]Toshiko Matsui, Yukino Baba, Toshihiro Kamishima, Hisashi Kashima:
Crowdordering. PAKDD (2) 2014: 336-347 - 2013
- [c54]Hiroshi Kajino, Yuta Tsuboi, Hisashi Kashima:
Clustering Crowds. AAAI 2013: 1120-1127 - [c53]Yukino Baba, Hisashi Kashima:
Statistical Quality Estimation for General Crowdsourcing Tasks. HCOMP (Works in Progress / Demos) 2013 - [c52]Toshiko Matsui, Yukino Baba, Toshihiro Kamishima, Hisashi Kashima:
Crowdsourcing Quality Control for Item Ordering Tasks. HCOMP (Works in Progress / Demos) 2013 - [c51]Satoshi Oyama, Yukino Baba, Yuko Sakurai, Hisashi Kashima:
EM-Based Inference of True Labels Using Confidence Judgments. HCOMP (Works in Progress / Demos) 2013 - [c50]Yukino Baba, Hisashi Kashima, Kei Kinoshita, Goushi Yamaguchi, Yosuke Akiyoshi:
Leveraging Crowdsourcing to Detect Improper Tasks in Crowdsourcing Marketplaces. IAAI 2013: 1487-1492 - [c49]Satoshi Oyama, Yukino Baba, Yuko Sakurai, Hisashi Kashima:
Accurate Integration of Crowdsourced Labels Using Workers' Self-reported Confidence Scores. IJCAI 2013: 2554-2560 - [c48]Yukino Baba, Hisashi Kashima:
Statistical quality estimation for general crowdsourcing tasks. KDD 2013: 554-562 - [c47]Yoshifumi Aimoto, Hisashi Kashima:
Matrix Factorization With Aggregated Observations. PAKDD (2) 2013: 521-532 - 2012
- [c46]Hiroshi Kajino, Yuta Tsuboi, Hisashi Kashima:
A Convex Formulation for Learning from Crowds. AAAI 2012: 73-79 - [c45]Nozomi Nori, Danushka Bollegala, Hisashi Kashima:
Multinomial Relation Prediction in Social Data: A Dimension Reduction Approach. AAAI 2012: 115-121 - [c44]Hiroshi Kajino, Yuta Tsuboi, Issei Sato, Hisashi Kashima:
Learning from Crowds and Experts. HCOMP@AAAI 2012 - [c43]Michael E. Houle, Hisashi Kashima, Michael Nett:
Generalized Expansion Dimension. ICDM Workshops 2012: 587-594 - [c42]Daisuke Kimura, Hisashi Kashima:
Fast Computation of Subpath Kernel for Trees. ICML 2012 - [c41]Shohei Hido, Hisashi Kashima:
Hash-based structural similarity for semi-supervised Learning on attribute graphs. ICPR 2012: 3009-3012 - [c40]Michael E. Houle, Hisashi Kashima, Michael Nett:
Fast Similarity Computation in Factorized Tensors. SISAP 2012: 226-239 - [c39]Kohei Hayashi, Takashi Takenouchi, Ryota Tomioka, Hisashi Kashima:
Self-measuring Similarity for Multi-task Gaussian Process. ICML Unsupervised and Transfer Learning 2012: 145-154 - 2011
- [c38]Yuta Tsuboi, Yuya Unno, Hisashi Kashima, Naoaki Okazaki:
Fast Newton-CG Method for Batch Learning of Conditional Random Fields. AAAI 2011: 489-494 - [c37]Satoshi Oyama, Kohei Hayashi, Hisashi Kashima:
Cross-Temporal Link Prediction. ICDM 2011: 1188-1193 - [c36]Xu Sun, Hisashi Kashima, Ryota Tomioka, Naonori Ueda, Ping Li:
A New Multi-task Learning Method for Personalized Activity Recognition. ICDM 2011: 1218-1223 - [c35]Ryota Tomioka, Taiji Suzuki, Kohei Hayashi, Hisashi Kashima:
Statistical Performance of Convex Tensor Decomposition. NIPS 2011: 972-980 - [c34]Daisuke Kimura, Tetsuji Kuboyama, Tetsuo Shibuya, Hisashi Kashima:
A Subpath Kernel for Rooted Unordered Trees. PAKDD (1) 2011: 62-74 - [c33]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 - [c32]Atsuhiro Narita, Kohei Hayashi, Ryota Tomioka, Hisashi Kashima:
Tensor Factorization Using Auxiliary Information. ECML/PKDD (2) 2011: 501-516 - 2010
- [c31]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 - [c30]Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya, Toshiyuki Tanaka:
Nonparametric Return Distribution Approximation for Reinforcement Learning. ICML 2010: 799-806 - [c29]Ryota Tomioka, Taiji Suzuki, Masashi Sugiyama, Hisashi Kashima:
A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices. ICML 2010: 1087-1094 - [c28]Mutsumi Fukuzaki, Mio Seki, Hisashi Kashima, Jun Sese:
Finding Itemset-Sharing Patterns in a Large Itemset-Associated Graph. PAKDD (2) 2010: 147-159 - [c27]Rudy Raymond, Hisashi Kashima:
Fast and Scalable Algorithms for Semi-supervised Link Prediction on Static and Dynamic Graphs. ECML/PKDD (3) 2010: 131-147 - [c26]Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya, Toshiyuki Tanaka:
Parametric Return Density Estimation for Reinforcement Learning. UAI 2010: 368-375 - 2009
- [c25]Mutsumi Fukuzaki, Mio Seki, Hisashi Kashima, Jun Sese:
Side Effect Prediction Using Cooperative Pathways. BIBM 2009: 142-147 - [c24]Shohei Hido, Hisashi Kashima:
A Linear-Time Graph Kernel. ICDM 2009: 179-188 - [c23]Masashi Sugiyama, Hirotaka Hachiya, Hisashi Kashima, Tetsuro Morimura:
Least absolute policy iteration for robust value function approximation. ICRA 2009: 2904-2909 - [c22]Hisashi Kashima, Satoshi Oyama, Yoshihiro Yamanishi, Koji Tsuda:
On Pairwise Kernels: An Efficient Alternative and Generalization Analysis. PAKDD 2009: 1030-1037 - [c21]Hisashi Kashima, Tsuyoshi Kato, Yoshihiro Yamanishi, Masashi Sugiyama, Koji Tsuda:
Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction. SDM 2009: 1100-1111 - 2008
- [c20]Yuta Tsuboi, Hisashi Kashima, Shinsuke Mori, Hiroki Oda, Yuji Matsumoto:
Training Conditional Random Fields Using Incomplete Annotations. COLING 2008: 897-904 - [c19]Shohei Hido, Yuta Tsuboi, Hisashi Kashima, Masashi Sugiyama, Takafumi Kanamori:
Inlier-Based Outlier Detection via Direct Density Ratio Estimation. ICDM 2008: 223-232 - [c18]Hisashi Kashima, Jianying Hu, Bonnie K. Ray, Moninder Singh:
K-means clustering of proportional data using L1 distance. ICPR 2008: 1-4 - [c17]Hisashi Kashima, Kazutaka Yamasaki, Akihiro Inokuchi, Hiroto Saigo:
Regression with interval output values. ICPR 2008: 1-4 - [c16]Yuta Tsuboi, Hisashi Kashima:
A new objective function for sequence labeling. ICPR 2008: 1-4 - [c15]Shohei Hido, Tsuyoshi Idé, Hisashi Kashima, Harunobu Kubo, Hirofumi Matsuzawa:
Unsupervised Change Analysis Using Supervised Learning. PAKDD 2008: 148-159 - [c14]Shohei Hido, Hisashi Kashima:
Roughly Balanced Bagging for Imbalanced Data. SDM 2008: 143-152 - [c13]Yuta Tsuboi, Hisashi Kashima, Shohei Hido, Steffen Bickel, Masashi Sugiyama:
Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation. SDM 2008: 443-454 - [c12]Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama:
Integration of Multiple Networks for Robust Label Propagation. SDM 2008: 716-726 - 2007
- [c11]Tsuyoshi Kato, Hisashi Kashima, Masashi Sugiyama, Kiyoshi Asai:
Multi-Task Learning via Conic Programming. NIPS 2007: 737-744 - [c10]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: 1433-1440 - 2006
- [c9]Hisashi Kashima, Naoki Abe:
A Parameterized Probabilistic Model of Network Evolution for Supervised Link Prediction. ICDM 2006: 340-349 - [c8]Hisashi Kashima:
Risk-Sensitive Learning via Expected Shortfall Minimization. SDM 2006: 529-533 - 2005
- [c7]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 - 2004
- [c6]Hisashi Kashima, Yuta Tsuboi:
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs. ICML 2004 - [c5]Tsuyoshi Idé, Hisashi Kashima:
Effective Dimension in Anomaly Detection: Its Application to Computer Systems. JSAI Workshops 2004: 189-204 - [c4]Tsuyoshi Idé, Hisashi Kashima:
Eigenspace-based anomaly detection in computer systems. KDD 2004: 440-449 - 2003
- [c3]Akihiro Inokuchi, Hisashi Kashima:
Mining Significant Pairs of Patterns from Graph Structures with Class Labels. ICDM 2003: 83-90 - [c2]Hisashi Kashima, Koji Tsuda, Akihiro Inokuchi:
Marginalized Kernels Between Labeled Graphs. ICML 2003: 321-328 - 2002
- [c1]Hisashi Kashima, Teruo Koyanagi:
Kernels for Semi-Structured Data. ICML 2002: 291-298
Editorship
- 2023
- [e7]Hisashi Kashima, Tsuyoshi Idé, Wen-Chih Peng:
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. Lecture Notes in Computer Science 13935, Springer 2023, ISBN 978-3-031-33373-6 [contents] - [e6]Hisashi Kashima, Tsuyoshi Idé, Wen-Chih Peng:
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. Lecture Notes in Computer Science 13936, Springer 2023, ISBN 978-3-031-33376-7 [contents] - [e5]Hisashi Kashima, Tsuyoshi Idé, Wen-Chih Peng:
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. Lecture Notes in Computer Science 13937, Springer 2023, ISBN 978-3-031-33379-8 [contents] - [e4]Hisashi Kashima, Tsuyoshi Idé, Wen-Chih Peng:
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. Lecture Notes in Computer Science 13938, Springer 2023, ISBN 978-3-031-33382-8 [contents] - 2022
- [e3]Yasufumi Takama, Naohiro Matsumura, Katsutoshi Yada, Mitsunori Matsushita, Daisuke Katagami, Akinori Abe, Hisashi Kashima, Toshihiro Hiraoka, Takahiro Uchiya, Rafal Rzepka:
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. Advances in Intelligent Systems and Computing 1423, Springer 2022, ISBN 978-3-030-96450-4 [contents] - 2021
- [e2]Katsutoshi Yada, Daisuke Katagami, Yasufumi Takama, Takayuki Ito, Akinori Abe, Eri Sato-Shimokawara, Junichiro Mori, Naohiro Matsumura, Hisashi Kashima:
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. Advances in Intelligent Systems and Computing 1357, Springer 2021, ISBN 978-3-030-73112-0 [contents] - 2012
- [e1]Tetsuo Shibuya, Hisashi Kashima, Jun Sese, Shandar Ahmad:
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 [contents]
Informal and Other Publications
- 2024
- [i47]Guoxi Zhang, Han Bao, Hisashi Kashima:
Online Policy Learning from Offline Preferences. CoRR abs/2403.10160 (2024) - [i46]Ryota Maruo, Hisashi Kashima:
Efficient Preference Elicitation in Iterative Combinatorial Auctions with Many Participants. CoRR abs/2403.19075 (2024) - [i45]Xiaotian Lu, Jiyi Li, Zhen Wan, Xiaofeng Lin, Koh Takeuchi, Hisashi Kashima:
Evaluating Saliency Explanations in NLP by Crowdsourcing. CoRR abs/2405.10767 (2024) - [i44]Shun Ito, Hisashi Kashima:
Mitigating Cognitive Biases in Multi-Criteria Crowd Assessment. CoRR abs/2407.18938 (2024) - [i43]Jiuding Duan, Jiyi Li, Yukino Baba, Hisashi Kashima:
A Generalized Model for Multidimensional Intransitivity. CoRR abs/2409.19325 (2024) - [i42]Xiaotian Lu, Jiyi Li, Koh Takeuchi, Hisashi Kashima:
AHP-Powered LLM Reasoning for Multi-Criteria Evaluation of Open-Ended Responses. CoRR abs/2410.01246 (2024) - 2023
- [i41]Xiaotian Lu, Jiyi Li, Koh Takeuchi, Hisashi Kashima:
Multiview Representation Learning from Crowdsourced Triplet Comparisons. CoRR abs/2302.03987 (2023) - [i40]Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima:
Mitigating Observation Biases in Crowdsourced Label Aggregation. CoRR abs/2302.13100 (2023) - [i39]Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima:
Mitigating Voter Attribute Bias for Fair Opinion Aggregation. CoRR abs/2307.10749 (2023) - [i38]Shin'ya Yamaguchi, Daiki Chijiwa, Sekitoshi Kanai, Atsutoshi Kumagai, Hisashi Kashima:
Regularizing Neural Networks with Meta-Learning Generative Models. CoRR abs/2307.13899 (2023) - [i37]Kosuke Yoshimura, Hisashi Kashima:
Label Selection Approach to Learning from Crowds. CoRR abs/2308.10396 (2023) - [i36]Jill-Jênn Vie, Hisashi Kashima:
Deep Knowledge Tracing is an implicit dynamic multidimensional item response theory model. CoRR abs/2309.12334 (2023) - [i35]Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu, Han Bao, Koh Takeuchi, Hisashi Kashima:
Estimating Treatment Effects Under Heterogeneous Interference. CoRR abs/2309.13884 (2023) - 2022
- [i34]Shin'ya Yamaguchi, Sekitoshi Kanai, Atsutoshi Kumagai, Daiki Chijiwa, Hisashi Kashima:
Transfer Learning with Pre-trained Conditional Generative Models. CoRR abs/2204.12833 (2022) - [i33]Yoichi Chikahara, Makoto Yamada, Hisashi Kashima:
Feature Selection for Discovering Distributional Treatment Effect Modifiers. CoRR abs/2206.00516 (2022) - [i32]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Twin Papers: A Simple Framework of Causal Inference for Citations via Coupling. CoRR abs/2208.09862 (2022) - [i31]Hisashi Kashima, Satoshi Oyama, Hiromi Arai, Junichiro Mori:
Trustworthy Human Computation: A Survey. CoRR abs/2210.12324 (2022) - [i30]Guoxi Zhang, Hisashi Kashima:
Behavior Estimation from Multi-Source Data for Offline Reinforcement Learning. CoRR abs/2211.16078 (2022) - [i29]Jill-Jênn Vie, Tomas Rigaux, Hisashi Kashima:
Variational Factorization Machines for Preference Elicitation in Large-Scale Recommender Systems. CoRR abs/2212.09920 (2022) - 2021
- [i28]Ayato Toyokuni, Sho Yokoi, Hisashi Kashima, Makoto Yamada:
Computationally Efficient Wasserstein Loss for Structured Labels. CoRR abs/2103.00899 (2021) - [i27]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 abs/2105.11152 (2021) - [i26]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Re-evaluating Word Mover's Distance. CoRR abs/2105.14403 (2021) - [i25]Luu Huu Phuc, Koh Takeuchi, Seiji Okajima, Arseny Tolmachev, Tomoyoshi Takebayashi, Koji Maruhashi, Hisashi Kashima:
Inter-domain Multi-relational Link Prediction. CoRR abs/2106.06171 (2021) - [i24]Xiaotian Lu, Arseny Tolmachev, Tatsuya Yamamoto, Koh Takeuchi, Seiji Okajima, Tomoyoshi Takebayashi, Koji Maruhashi, Hisashi Kashima:
Crowdsourcing Evaluation of Saliency-based XAI Methods. CoRR abs/2107.00456 (2021) - [i23]Guoxi Zhang, Hisashi Kashima:
Batch Reinforcement Learning from Crowds. CoRR abs/2111.04279 (2021) - [i22]Sein Minn, Jill-Jênn Vie, Koh Takeuchi, Hisashi Kashima, Feida Zhu:
Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations. CoRR abs/2112.11209 (2021) - 2020
- [i21]Ryoma Sato, Marco Cuturi, Makoto Yamada, Hisashi Kashima:
Fast and Robust Comparison of Probability Measures in Heterogeneous Spaces. CoRR abs/2002.01615 (2020) - [i20]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Random Features Strengthen Graph Neural Networks. CoRR abs/2002.03155 (2020) - [i19]Shonosuke Harada, Hisashi Kashima:
Counterfactual Propagation for Semi-Supervised Individual Treatment Effect Estimation. CoRR abs/2005.05099 (2020) - [i18]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Fast Unbalanced Optimal Transport on Tree. CoRR abs/2006.02703 (2020) - [i17]Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima:
Regret Minimization for Causal Inference on Large Treatment Space. CoRR abs/2006.05616 (2020) - [i16]Yukino Baba, Jiyi Li, Hisashi Kashima:
CrowDEA: Multi-view Idea Prioritization with Crowds. CoRR abs/2008.02354 (2020) - [i15]Yang Liu, Hisashi Kashima:
Chemical Property Prediction Under Experimental Biases. CoRR abs/2009.08687 (2020) - [i14]Shonosuke Harada, Hisashi Kashima:
GraphITE: Estimating Individual Effects of Graph-structured Treatments. CoRR abs/2009.14061 (2020) - [i13]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Poincare: Recommending Publication Venues via Treatment Effect Estimation. CoRR abs/2010.09157 (2020) - 2019
- [i12]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Constant Time Graph Neural Networks. CoRR abs/1901.07868 (2019) - [i11]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 abs/1902.01148 (2019) - [i10]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Learning to Find Hard Instances of Graph Problems. CoRR abs/1902.09700 (2019) - [i9]Tatsuya Shiraishi, Tam Le, Hisashi Kashima, Makoto Yamada:
Topological Bayesian Optimization with Persistence Diagrams. CoRR abs/1902.09722 (2019) - [i8]Ryoma Sato, Makoto Yamada, Hisashi Kashima:
Approximation Ratios of Graph Neural Networks for Combinatorial Problems. CoRR abs/1905.10261 (2019) - 2018
- [i7]Hirotaka Akita, Kosuke Nakago, Tomoki Komatsu, Yohei Sugawara, Shin-ichi Maeda, Yukino Baba, Hisashi Kashima:
BayesGrad: Explaining Predictions of Graph Convolutional Networks. CoRR abs/1807.01985 (2018) - [i6]Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki, Yukino Baba, Ichigaku Takigawa, Yoshihiro Yamanishi, Hisashi Kashima:
Dual Convolutional Neural Network for Graph of Graphs Link Prediction. CoRR abs/1810.02080 (2018) - [i5]Jill-Jênn Vie, Hisashi Kashima:
Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing. CoRR abs/1811.03388 (2018) - 2017
- [i4]Jill-Jênn Vie, Florian Yger, Ryan Lahfa, Basile Clement, Kévin Cocchi, Thomas Chalumeau, Hisashi Kashima:
Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario. CoRR abs/1709.01584 (2017) - 2015
- [i3]Junpei Komiyama, Junya Honda, Hisashi Kashima, Hiroshi Nakagawa:
Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem. CoRR abs/1506.02550 (2015) - 2012
- [i2]Tetsuro Morimura, Masashi Sugiyama, Hisashi Kashima, Hirotaka Hachiya, Toshiyuki Tanaka:
Parametric Return Density Estimation for Reinforcement Learning. CoRR abs/1203.3497 (2012) - [i1]Daisuke Kimura, Hisashi Kashima:
Fast Computation of Subpath Kernel for Trees. CoRR abs/1206.4642 (2012)
Coauthor Index
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