2024
Journal
International Conference
- Yohei Kodama, Yuki Akeyama, Yusuke Miyazaki, Koh Takeuchi. Travel Demand Prediction with Application to Commuter Demand Estimation on Urban Railways.
In Proceedings of the 2024 ACM Web Conference (WWW), 2024. - Yu Mitsuzumi, Akisato Kimura, Hisashi Kashima.
Understanding and Improving Source-free Domain Adaptation from a Theoretical Perspective.
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024. - Shin’ya Yamaguchi, Sekitoshi Kanai, Kazuki Adachi, Daiki Chijiwa.
Adaptive Random Feature Regularization on Fine-tuning Deep Neural Networks.
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024. - Xiaotian Lu, Jiyi Li, Zhen Wan, Xiaofeng Lin, Koh Takeuchi, Hisashi Kashima.
Evaluating Saliency Explanations in NLP by Crowdsourcing.
In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING), 2024. - Yuki Wakai, Koh Takeuchi, Hisashi Kashima.
Recovering Population Dynamics from a Single Point Cloud Snapshot.
In Proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2024. - Lin Xiaofeng, Hisashi Kashima.
Treatment Effect Estimation Under Unknown Interference.
In Proceedings of the 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2024.
2023
Journal
- Yuki Takezawa, Han Bao, Kenta Niwa, Ryoma Sato, Makoto Yamada.
Momentum Tracking: Momentum Acceleration for Decentralized Deep Learning on Heterogeneous Data.
Transactions on Machine Learning Research, 2023.
International Conference
- Sho Otao, Makoto Yamada.
A linear time approximation of Wasserstein distance with word embedding selection.
In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023. - Yuki Takezawa, Ryoma Sato, Han Bao, Kenta Niwa, Makoto Yamada
Beyond Exponential Graph: Communication-Efficient Topologies for Decentralized Learning via Finite-time Convergence.
In Advances in Neural Information Processing Systems (NeurIPS), 2023. - Shin’ya Yamaguchi, Daiki Chijiwa, Sekitoshi Kanai, Atsutoshi Kumagai, Hisashi Kashima.
Regularizing Neural Networks with Meta-Learning Generative Models.
In Advances in Neural Information Processing Systems (NeurIPS), 2023. - Shin’ya Yamaguchi.
Generative Semi-supervised Learning with Meta-Optimized Synthetic Samples.
In Proceedings of the 15th Asian Conference on Machine Learning (ACML), 2023. - Akihiro Yamaguchi, Ken Ueno, Hisashi Kashima.
Time-series Shapelets with Learnable Lengths.
In Proceedings of the 32nd ACM International Conference on Information and Knowledge Management (CIKM), 2023. - Kosuke Yoshimura, Hisashi Kashima.
Label Selection Approach to Learning from Crowds.
In Proceedings of the 30th International Conference on Neural Information Processing (ICONIP), 2023. - Ryuichiro Hataya, Han Bao, Hiromi Arai.
Will Large-scale Generative Models Corrupt Future Datasets?
In Proceedings of IEEE International Conference on Computer Vision (ICCV), 2023. - Jill-Jênn Vie, Hisashi Kashima.
Deep Knowledge Tracing is an Implicit Dynamic Multidimensional Item Response Theory Model.
In Proceedigs of the 31st International Conference on Computers in Education (ICCE), 2023. - Xiaofeng Lin, Guoxi Zhang, Xiaotian Lu, Han Bao, Koh Takeuchi, Hisashi Kashima.
Estimating Treatment Effects Under Heterogeneous Interference.
In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2023. - Koh Takeuchi, Ryo Nishida, Hisashi Kashima, Masaki Onishi.
Causal Effect Estimation on Hierarchical Spatial Graph Data.
In Proceedings of the 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2023. - Ryu Shirakami, Toshiya Kitahara, Koh Takeuchi, Hisashi Kashima.
QTNet: Theory-based Queue Length Prediction for Urban Traffic.
In Proceedings of the 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2023. - Han Bao.
Proper Losses, Moduli of Convexity, and Surrogate Regret Bounds.
In Proceedings of the 36th Conference on Learning Theory (COLT), 2023. - Yuki Arase, Han Bao, Sho Yokoi.
Unbalanced Optimal Transport for Unbalanced Word Alignment.
In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL), 2023. - Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima.
Fair Opinion Aggregation for Voter Attribute Bias.
In Proceedings of 6th AAAI/ACM Conference on AI, Ethics, and Society (AIES), 2023. - Ryoma Sato.
Graph Neural Networks can Recover the Hidden Features Solely from the Graph Structure.
In Proceedings of the 40th International Conference on Machine Learning (ICML), 2023. - Xiaotian Lu, Jiyi Li, Koh Takeuchi, Hisashi Kashima.
Multiview Representation Learning from Crowdsourced Triplet Comparisons.
In Proceedings of the Web Conference (WWW), 2023. - Ryoma Sato.
Active Learning from the Web.
In Proceedings of the Web Conference (WWW), 2023. - Guoxi Zhang, Hisashi Kashima.
Behavior Estimation from Multi-Source Data for Offline Reinforcement Learning.
In Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), 2023.
2022
Journal
- Guoxi Zhang, Hisashi Kashima.
Learning State Importance for Preference-based Reinforcement Learning.
Machine Learning, 2022. - Shonosuke Harada, Hisashi Kashima.
InfoCEVAE: Treatment Effect Estimation with Hidden Confounding Variables Matching.
Machine Learning, 2022. - Yoichi Chikahara, Shinsaku Sakaue, Akinori Fujino, Hisashi Kashima.
Making Individually Fair Predictions with Causal Pathways.
Data Mining and Knowledge Discovery (DAMI), 2022. - Yang Liu, Hisashi Kashima.
Chemical Property Prediction Under Experimental Biases.
Scientific Reports, 2022. - Akira Tanimoto, So Yamada, Takashi Takenouchi, Masashi Sugiyama, Hisashi Kashima.
Improving Imbalanced Classification Using Near-miss Instances.
Expert Systems with Applications (ESWA), 2022. - Ryoma Sato, Makoto Yamada, Hisashi Kashima.
Poincare: Recommending Publication Venues via Treatment Effect Estimation.
Journal of Informetrics, 2022. - Maya Okawa, Tomoharu Iwata, Yusuke Tanaka, Hiroyuki Toda, Takeshi Kurashima, Hisashi Kashima.
Context-aware Spatio-temporal Event Prediction via Convolutional Hawkes Processes.
Machine Learning, 2022. - Naoya Takeishi, Keisuke Fujii, Koh Takeuchi, Yoshinobu Kawahara.
Discriminant Dynamic Mode Decomposition for Labeled Spatio-Temporal Data Collections.
SIAM Journal on Applied Dynamical Systems (SIADS), 2022. - Ryoma Sato, Makoto Yamada, Hisashi Kashima.
Constant Time Graph Neural Networks.
ACM Transactions on Knowledge Discovery from Data (TKDD), 2022.
International Conference
- Jill-Jênn Vie, Tomas Rigaux, Hisashi Kashima.
Variational Factorization Machines for Preference Elicitation in Large-Scale Recommender Systems.
In Proceedings of the 2022 IEEE International Conference on Big Data (BigData), 2022. - Guoxi Zhang, Jiyi Li, Hisashi Kashima.
Improving Pairwise Rank Aggregation via Querying for Rank Difference.
In Proceedings of the 9th IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2022. - Ryoma Sato.
Towards Principled User-side Recommender Systems.
In Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM), 2022. - Ryoma Sato.
CLEAR: A Fully User-side Image Search System.
In Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM), 2022. - Ryoma Sato, Makoto Yamada, Hisashi Kashima.
Twin Papers: A Simple Framework of Causal Inference for Citations via Coupling.
In Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM), 2022. - Guoxi Zhang, Hisashi Kashima.
Batch Reinforcement Learning from Crowds.
In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2022. - Mathis Petrovich, Chao Liang, Ryoma Sato, Yanbin Liu, Yao-Hung Hubert Tsai, Linchao Zhu, Yi Yang, Ruslan Salakhutdinov, Makoto Yamada.
Feature Robust Optimal Transport for High-dimensional Data.
In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2022. - Hiroshi Takahashi, Tomoharu Iwata, Atsutoshi Kumagai, Sekitoshi Kanai, Masanori Yamada, Yuuki Yamanaka, Hisashi Kashima.
Learning Optimal Priors for Task-Invariant Representations in Variational Autoencoders.
In Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2022. - Ryosuke Ueda, Koh Takeuchi, Hisashi Kashima.
Mitigating Observation Biases in Crowdsourced Label Aggregation.
In Proceedings of the 26th International Conference on Pattern Recognition (ICPR), 2022. - Yoichi Chikahara, Makoto Yamada, Hisashi Kashima.
Feature Selection for Discovering Distributional Treatment Effect Modifiers.
In Proceedings of the 38th Conference on Uncertaintly in Artificial Intelligence (UAI), 2022. - Ryoma Sato, Makoto Yamada, Hisashi Kashima.
Re-evaluating Word Mover’s Distance.
In Proceedings of the 39th International Conference on Machine Learning (ICML), 2022. - Ryoma Sato.
Word Tour: One-dimensional Word Embeddings via the Traveling Salesman Problem.
In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL), 2022. - Yuki Takezawa, Ryoma Sato, Zornitsa Kozareva, Sujith Ravi, Makoto Yamada.
Fixed Support Tree-Sliced Wasserstein Barycenter.
In Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 2022. - Benjamin Poignard, Peter Naylor, Héctor Climente, Makoto Yamada.
Feature Screening with Kernel Knockoff.
In Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (AISTATS), 2022. - Ryoma Sato.
Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data?
In Proceedings of the SIAM International Conference on Data Mining (SDM), 2022. - Akihiro Yamaguchi, Ken Ueno, Hisashi Kashima.
Learning Time-series Shapelets Enhancing Discriminability.
In Proceedings of the SIAM International Conference on Data Mining (SDM), 2022. - Sein Minn, Jill-Jenn Vie, Koh Takeuchi, Hisashi Kashima, Feida Zhu.
Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations.
In Proceedings of the 12th AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI), 2022. - Akihiro Yamguchi, Ken Ueno, Hisashi Kashima.
Learning Evolvable Time-series Shapelets.
In Proceedings of the 38th International Conference on Data Engineering (ICDE), 2022. - Ryoma Sato.
Enumerating Fair Packages for Group Recommendations.
In Proceedings of the 15th International Conference on Web Search and Data Mining (WSDM), 2022. - Ryoma Sato.
Retrieving Black-box Optimal Images from External Databases.
In Proceedings of the 15th International Conference on Web Search and Data Mining (WSDM), 2022.
2021
Journal
- Naoki Miyaguchi, Koh Takeuchi, Hisashi Kashima, Mizuki Morita, Hiroshi Morimatsu.
Predicting Anesthetic Infusion Events Using Machine Learning.
Scientific Reports, 2021. - Shogo Hayashi, Junya Honda, Hisashi Kashima.
Bayesian Optimization with Partially Specified Queries.
Machine Learning, 2021. - Jiuding Duan, Hisashi Kashima.
Learning to Rank for Multi-step Ahead Time-Series Forecasting.
IEEE Access, 2021. - Akira Tanimoto.
Combinatorial Q-Learning for Condition-based Infrastructure Maintenance.
IEEE Access, 2021.
International Conference
- Hiroaki Yamada, Makoto Yamada.
Dynamic Sasvi: Strong Safe Screening for Norm-Regularized Least Squares
Advances in Neural Information Processing Systems (NeurIPS), 2021 - Tam Le, Truyen Nguyen, Makoto Yamada, Jose Blanchet, Viet Anh Nguyen.
Adversarial Regression with Doubly Non-negative Weighting Matrices
Advances in Neural Information Processing Systems (NeurIPS), 2021 - Jiyi Li, Lucas Ryo Endo, Hisashi Kashima.
Label Aggregation for Crowdsourced Triplet Similarity Comparisons.
In Proceedings of the 28th International Conference on Neural Information Processing (ICONIP), 2021. - Koh Takeuchi, Masaaki Imaizumi, Shunsuke Kanda, Keisuke Fujii, Masakazu Ishihata, Takuya Maekawa, Ken Yoda, Yasuo Tabei.
Fréchet Kernel for Trajectory Data Analysis.
In Proceedings of 29th ACM International Conference on Advances in Geographic Information Systems (SIGSPATIAL), 2021. - Shonosuke Harada, Hisashi Kashima.
GraphITE: Estimating Individual Effects of Graph-structured Treatments.
In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM), 2021. - Toshihiro Kamishima, Shotaro Akaho, Yukino Baba, Hisashi Kashima.
Preliminary Experiments to Examine the Stability of Bias-Aware Techniques.
In Proceedings of the 2nd International Workshop on Algorithmic Bias in Search and Recommendation (BIAS), 2021. - Takako Onishi, Hisashi Kashima.
Machine Failure Diagnosis by Combining Software Log and Sensor Data.
In Proceedings of IEEE International Conference on Electrical, Control and Instrumentation Engineering (ICECIE), 2021. - Lu Xiaotian, Arseny Tolmachev, Tatsuya Yamamoto, Koh Takeuchi, Seiji Okajima, Tomoyoshi Takebayashi, Koji Maruhashi, Hisashi Kashima.
Crowdsourcing Evaluation of Saliency-based XAI Methods.
In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2021. - Luu Huu Phuc, Koh Takeuchi, Seiji Okajima, Arseny Tolmachev, Tomoyoshi Takebayashi, Koji Maruhashi, Hisashi Kashima.
Inter-domain Multi-relational Link Prediction.
In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2021. - Yanbin Liu, Makoto Yamada, Yao-Hung Hubert Tsai, Tam Le, Ruslan Salakhutdinov, Yi Yang.
LSMI-Sinkhorn: Semi-supervised Squared-Loss Mutual Information Estimation with Optimal Transport.
In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 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.
In Proceedings of the 24th IEEE International Intelligent Transportation Systems Conference (ITSC), 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.
In Proceedings of the 27st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021. - Yuki Takezawa, Ryoma Sato, Makoto Yamada
Supervised Tree-Wasserstein Distance.
In Proceedings of the 38th International Conference on Machine Learning (ICML), 2021. - Tobias Freidling, Benjamin Poignard, Héctor Climente-González, Makoto Yamada
Post-selection inference with HSIC-Lasso.
In Proceedings of the 38th International Conference on Machine Learning (ICML), 2021. - Vu Nguyen, Tam Le, Makoto Yamada, Michael A Osborne
Optimal Transport Kernels for Sequential and Parallel Neural Architecture Search.
In Proceedings of the 38th International Conference on Machine Learning (ICML), 2021. - Ayato Toyokuni, Sho Yokoi, Hisashi Kashima, Makoto Yamada
Computationally Efficient Wasserstein Loss for Structured Labels
EACL SRW 2021 - Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima.
Causal Combinatorial Factorization Machines for Set-wise Recommendation.
In Proceedings of the 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2021. - Akira Tanimoto, Tomoya Sakai, Takashi Takenouchi, Hisashi Kashima.
Regret Minimization for Causal Inference on Large Treatment Space.
In Proceedings of The 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 2021. - Yoichi Chikahara, Shinsaku Sakaue, Akinori Fujino, Hisashi Kashima.
Learning Individually Fair Classifier with Path-Specific Causal-Effect Constraint.
In Proceedings of The 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 2021. - Tam Le, Nhat Ho, Makoto Yamada.
Flow-based Alignment Approaches for Probability Measures in Different Spaces.
In Proceedings of The 24th International Conference on Artificial Intelligence and Statistics (AISTATS), 2021. - Ryoma Sato, Makoto Yamada, Hisashi Kashima.
Random Features Strengthen Graph Neural Networks.
In Proceedings of SIAM International Conference on Data Mining (SDM), 2021. - Koh Takeuchi, Ryo Nishida, Hisashi Kashima, Masaki Onishi.
Grab the Reins of Crowds: Estimating the Effects of Crowd Movement Guidance Using Causal Inference.
In Proceedings of 20th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2021.
2020
Journal
- Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki, Yukino Baba, Ichigaku Takigawa, Yoshihiro Yamanishi, Hisashi Kashima. Dual Graph Convolutional Neural Network for Predicting Chemical Networks. BMC Bioinformatics (presented at GIW/ABACBS 2019), 2020.
- Eli Kaminuma, Yukino Baba, Masahiro Mochizuki, Hirotaka Matsumoto, Haruka Ozaki, Toshitsugu Okayama, Takuya Kato, Shinya Oki, Takatomo Fujisawa, Yasukazu Nakamura, Masanori Arita, Osamu Ogasawara, Hisashi Kashima, Toshihisa Takagi.
DDBJ Data Analysis Challenge: A Machine Learning Competition to Predict Arabidopsis Chromatin Feature Annotations from DNA Sequences.
Genes & Genetic Systems, Vol. 95, 2020. - Shun Ito, Yukino Baba, Tetsu Isomura, Hisashi Kashima.
Synthetic Accessibility Assessment Using Auxiliary Responses.
Expert Systems with Applications (ESWA), 2020.
International Conference
- Ryoma Sato, Makoto Yamada, Hisashi Kashima.
Fast Unbalanced Optimal Transport on Tree.
Advances in Neural Information Processing Systems (NeurIPS 2020). - Yao-Hung Hubert Tsai, Han Zhao, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov.
Neural Methods for Point-wise Dependency Estimation
Advances in Neural Information Processing Systems (NeurIPS 2020). - Shunsuke Kanda, Koh Takeuchi, Keisuke Fujii, Yasuo Tabei.
Succinct Trit-array Trie for Scalable Trajectory Similarity Search.
In Proceedings of 28th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL), 2020. - Luu Huu Phuc, Koh Takeuchi, Makoto Yamada, Hisashi Kashima.
Simultaneous Link Prediction on Unaligned Networks Using Graph Embedding and Optimal Transport.
In Proceedings of the the 7th IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2020. - Hitoshi Kusano, Yuji Horiguchi, Yukino Baba and Hisashi Kashima.
Stress Prediction from Head Motion.
In Proceedings of the the 7th IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2020. - Yukino Baba, Jiyi Li, Hisashi Kashima.
CrowDEA: Multi-view Idea Prioritization with Crowds.
In Proceedings of the 8th AAAI Conference on Human Computation and Crowdsourcing (HCOMP), 2020. - Yan Gu, Jiuding Duan, Hisashi Kashima.
An Intransitivity Model for Matchup and Pairwise Comparison.
In Proceedings of the 25th International Conference on Pattern Recognition (ICPR), 2020. - Shounosuke Harada, Hisashi Kashima.
Counterfactual Propagation for Semi-Supervised Individual Treatment Effect Estimation.
In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2020. - Yasutoshi Ida, Sekitoshi Kanai,Yasuhiro Fujiwara, Tomoharu Iwata, Koh Takeuchi, Hisashi Kashima.
Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance.
In Proceedings of the 37th International Conference on Machine Learning (ICML), 2020. - Jiyi Li, Yasushi Kawase, Yukino Baba, Hisashi Kashima.
Performance as a Constraint: An Improved Wisdom of Crowds Using Performance Regularization.
In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI), pp.XX-XX, 2020. - Yanbin Liu, Linchao Zhu, Makoto Yamada, Yi Yang.
Semantic Correspondence as an Optimal Transport Problem
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020. - Tatsuya Shiraishi, Tam Le, Hisashi Kashima, Makoto Yamada
Topological Bayesian Optimization with Persistence Diagrams.
In Proceedings of the 24th European Conference on Artificial Intelligence (ECAI), 2020. - Benjamin Poignard, Makoto Yamada
Sparse Hilbert-Schmidt Independence Criterion Regression.
In Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 2020. - Jenning Lim, Makoto Yamada, Wittawat Jitkrittum, Yoshikazu Terada, Shigeyuki Matsui, Hidetoshi Shimodaira
More Powerful Selective Kernel Tests for Feature Selection
In Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS), 2020. - Qiang Huang, TingYu Xia, HuiYan Sun, Makoto Yamada, Yi Chang.
Unsupervised Nonlinear Feature Selection from High-dimensional Signed Networks
In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020.
Preprints
- Ryoma Sato.
A Survey on The Expressive Power of Graph Neural Networks. - Ryoma Sato, Marco Cuturi, Makoto Yamada, Hisashi Kashima.
Fast and Robust Comparison of Probability Measures in Heterogeneous Spaces.
2019
Journal
- Kishan, Wimalawarne, Makoto Yamada, Hiroshi Mamitsuka.
Scaled Coupled Norms and Coupled Higher Order Tensor Completion.
Neural Computation (NECO), 2019. - Yu Saito, Kento Shin, Kei Terayama, Shaan Desai, Masaru Onga, Yuji Nakagawa, Yuki M. Itahashi, Yoshihiro Iwasa, Makoto Yamada, Koji Tsuda
Deep-learning-based quality filtering of mechanically exfoliated 2D crystals
npj Computational Materials volume 5, Article number: 124 (2019) - Héctor Climente, Chloé-Agathe Azencott, Samuel Kaski, Makoto Yamada. Block HSIC Lasso: model-free biomarker detection for ultra-high dimensional data. Bioinformatics (presented at ISMB 2019), 2019.
- Akihiro Isozaki, Hideharu Mikami, Kotaro Hiramatsu, Shinya Sakuma, Yusuke Kasai, Takanori Iino, Takashi Yamano, Atsushi Yasumoto, Yusuke Oguchi, Nobutake Suzuki, Yoshitaka Shirasaki, Taichiro Endo, Takuro Ito, Kei Hiraki, Makoto Yamada, Satoshi Matsusaka, Takeshi Hayakawa, Hideya Fukuzawa, Yutaka Yatomi, Fumihito Arai, Dino Di Carlo, Atsuhiro Nakagawa, Yu Hoshino, Yoichiroh Hosokawa, Sotaro Uemura, Takeaki Sugimura, Yasuyuki Ozeki, Nao Nitta, Keisuke Goda.
A practical guide to intelligent image-activated cell sorting
Nature Protocols, 2019. - Hirofumi Kobayashi, Cheng Lei, Yi Wu, Chun-Jung Huang, Atsushi Yasumoto, Masahiro Jona, Wenxuan Li, Yunzhao Wu, Yaxiaer Yalikun, Yiyue Jiang, Baoshan Guo, Chia-Wei Sun, Yo Tanaka, Makoto Yamada, Yutaka Yatomif, Keisuke Goda
Intelligent whole-blood imaging flow cytometry for simple, rapid, and cost-effective drug-susceptibility testing of leukemia
Lab on a Chip, 2019.
International Conference
- Ryoma Sato, Makoto Yamada, Hisashi Kashima.
Approximation Ratios of Graph Neural Networks for Combinatorial Problems.
Advances in Neural Information Processing Systems (NeurIPS), 2019. - Yasutoshi Ida, Yasuhiro Fujiwara, Hisashi Kashima.
Fast Sparse Group Lasso.
Advances in Neural Information Processing Systems (NeurIPS), 2019. - Tam Le, Makoto Yamada, Kenji Fukumizu, Marco Cuturi.
Tree-Sliced Variants of Wasserstein Distances.
Advances in Neural Information Processing Systems (NeurIPS), 2019. - Jenning Lim, Makoto Yamada, Bernhard Schoelkopf, Wittawat Jitkrittum
Kernel Stein Tests for Multiple Model Comparison.
Advances in Neural Information Processing Systems (NeurIPS), 2019. - Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric Gouy-Pailler, Jamal Atif.
Theoretical Evidence for Adversarial Robustness Through Randomization.
Advances in Neural Information Processing Systems (NeurIPS), 2019. - Shogo Hayashi, Yoshinobu Kawahara, Hisashi Kashima.
Active Change-Point Detection.
In Proceedings of the 11th Asian Conference on Machine Learning (ACML), 2019. - Ryoma Sato, Makoto Yamada, Hisashi Kashima.
Learning to Sample Hard Instances for Graph Algorithms.
In Proceedings of the 11th Asian Conference on Machine Learning (ACML), 2019. - Yao-Hung Hubert Tsai, Shaojie Bai, Makoto Yamada, Louis-Philippe Morency and Ruslan Salakhutdinov.
Empirical Study of Transformer’s Attention Mechanism via the Lens of Kernel Empirical Methods in Natural Language Processing (EMNLP), 2019. - Shonosuke Harada, Kazuki Taniguchi, Makoto Yamada, Hisashi Kashima.
Context-Regularized Neural Collaborative Filtering for Game App Recommendation
ACM RecSys LBR track, 2019. - Daiki Tanaka, Makoto Yamada, Hisashi Kashima, Takeshi Kishikawa, Tomoyuki Haga, Takamitsu Sasaki.
In-Vehicle Network Intrusion Detection andExplanation Using Density Ratio Estimation.
In Proceedings of 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2019. - Daiki Tanaka, Yukino Baba, Kashima Hisashi, Yuta Okubo.
Large-scale Driver Identification Using Automobile Driving Data.
In Proceedings of 2019 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2019. - Shonosuke Harada, Kazuki Taniguchi, Makoto Yamada, Hisashi Kashima.
In-app Purchase Prediction Using Bayesian Personalized Dwell Day Ranking.
In Proceedings of AdKDD 2019 Workshop (AdKDD), 2019. - Kosuke Yoshimura, Tomoaki Iwase, Yukino Baba, Hisashi Kashima.
Interdependence Model for Multi-label Classification.
In Proceedings of the 28th International Conference on Artificial Neural Networks (ICANN), 2019. - Takeru Sunahase, Yukino Baba, Hisashi Kashima.
Probabilistic Modeling of Peer Correction and Peer Assessment.
In Proceedings of the 12th International Conference on Educational Data Mining (EDM), 2019. - Shogo Hayashi, Akira Tanimoto, Hisashi Kashima.
Long-Term Prediction of Small Time-Series Data Using Generalized Distillation.
In Proceedings of the 2019 International Joint Conference on Neural Networks (IJCNN), 2019. - Yusuke Sakata, Yukino Baba, Hisashi Kashima.
CrowNN: Human-in-the-loop Network with Crowd Crowd-generated Inputs.
In Proceedings of the 44th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019. - Makoto Yamada*, Denny Wu*, Yao-Hung Hubert Tsai, Hirofumi Ohta, Ruslan Salakhutdinov, Ichiro Takeuchi, Kenji Fukumizu (* equal contribution)
Post Selection Inference with Incomplete Maximum Mean Discrepancy Estimator.
In Proceedings of the 7th International Conference on Learning Representations (ICLR), 2019. - Jill-Jênn Vie, Hisashi Kashima.
Factorization Machines for Knowledge Tracing.
In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI), 2019.
2018
Journal
- Nao Nitta, Takeaki Sugimura, Akihiro Isozaki, Hideharu Mikami, Kei Hiraki, Shinya Sakuma, Takanori Iino, Fumihito Arai, Taichiro Endo, Yasuhiro Fujiwaki, Hideya Fukuzawa, Misa Hase, Takeshi Hayakawa, Kotaro Hiramatsu, Yu Hoshino, Mary Inaba, Takuro Ito, Hiroshi Karakawa, Yusuke Kasai, Kenichi Koizumi, SangWook Lee, Cheng Lei, Ming Li, Takanori Maeno, Satoshi Matsusaka, Daichi Murakami, Atsuhiro Nakagawa, Yusuke Oguchi, Minoru Oikawa, Tadataka Ota, Kiyotaka Shiba, Hirofumi Shintaku, Yoshitaka Shirasaki, Kanako Suga, Yuta Suzuki, Nobutake Suzuki, Yo Tanaka, Hiroshi Tezuka, Chihana Toyokawa, Yaxiaer Yalikun, Makoto Yamada, Mai Yamagishi, Takashi Yamano, Atsushi Yasumoto, Yutaka Yatomi, Masayuki Yazawa, Dino Di Carlo, Yoichiroh Hosokawa, Yasuyuki Ozeki, Keisuke Goda.
Intelligent Image-Activated Cell Sorting.
Cell, Volume 175, ISSUE 1, P266-276.e13, September 20, 2018. - Cheng Lei, Hirofumi Kobayashi, Yi Wu, Ming Li, Akihiro Isozaki, Atsushi Yasumoto, Hideharu Mikami, Takuro Ito, Nao Nitta, Takeaki Sugimura, Makoto Yamada, Yutaka Yatomi, Dino Di Carlo, Yasuyuki Ozeki, Keisuke Goda.
High-throughput imaging flow cytometry by optofluidic time-stretch microscopy.
Nature Protocols. volume 13, pages1603–1631, 2018. - Heewon Park, Makoto Yamada, Seiya Imoto, Satoru Miyano.
Robust sample-specific stability selection with effective error control.
Journal of Computational Biology, 2018. - Kishan Wimarawarne, Makoto Yamada, Hiroshi Mamitsuka.
Convex Coupled Matrix and Tensor Completion.
Neural Computation, 2018. - Makoto Yamada, Jiliang Tang, Jose Lugo-Martinez, Ermin Hodzic, Raunak Shrestha, Avishek Saha, Hua Ouyang, Dawei Yin, Hiroshi Mamitsuka, Cenk Sahinalp, Predrag Radivojac, Philipo Menczer, Yi Chang.
Ultra High-Dimensional Nonlinear Feature Selection for Big Biological Data.
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2018. - Yue Wang, Dawei Yin, Roger Jie Luo, Penguyan Wnag, Makoto Yamada, Yi Chang, Qiaozhu Mei.
Optimizing Whole-Page Presentation for Web Search.
ACM Transactions on the Web (TWEB), 2018. - Yukino Baba, Tetsu Isomura, Hisashi Kashima.
Wisdom of Crowds for Synthetic Accessibility Evaluation.
Journal of Molecular Graphics and Modelling, Vol.80, pp.217-223, 2018. - Atsuto Seko, Hiroyuki Hayashi, Hisashi Kashima, Isao Tanaka.
Matrix- and Tensor-based Recommender Systems for the Discovery of Currently Unknown Inorganic Compounds.
Physical Review Materials, Vol.2, No.1, 2018. - Takuya Kuwahara, Yukino Baba, Hisashi Kashima, Takeshi Kishikawa, Junichi Tsurumi, Tomoyuki Haga, Yoshihiro Ujiie, Takamitsu Sasaki, Hideki Matsushima.
Supervised and Unsupervised Intrusion Detection Based on CAN Message Frequencies for In-Vehicle Network.
Journal of Information Processing, 2018.
International Conference
- Tam Le, Makoto Yamada.
Persistence Fisher Kernel: A Riemannian Manifold Kernel for Persistence Diagrams.
In Proceedings of the Advances in Neural Information Processing Systems (NeurIPS 2018). - Tanmoy Mukherjee, Makoto Yamada, Timothy Hospedales.
Learning UnsupervisedWord TranslationsWithout Adversaries.
In Proceedings of the conference on Empirical Methods in Natural Language Processing (EMNLP), 2018. - Kosuke Kikui, Yuta Itoh, Makoto Yamada, Yuta Sugiura, Maki Sugimoto.
Intra-/Inter-user Adaptation Framework for Wearable Gesture Sensing Device.
In Proceedings of the International Symposium on Wearable Computers (ISWC) 2018. - Hirotaka Akita, Kosuke Nakago, Tomoki Komatsu, Yohei Sugawara, Shin-ichi Maeda, Yukino Baba, Hisashi Kashima.
BayesGrad: Explaining Predictions of Graph Convolutional Networks.
In Proceedings of the 25th International Conference on Neural Information Processing (ICONIP), 2018. - Ryoma Sato, Takehiro Yamamoto, Hisashi Kashima.
Short-term Precipitation Prediction with Skip-connected PredNet.
In Proceedings of the 27th International Conference on Artificial Neural Networks (ICANN), 2018. - Jiyi Li, Hisashi Kashima.
Incorporating Worker Similarity for Label Aggregation in Crowdsourcing.
In Proceedings of the 27th International Conference on Artificial Neural Networks (ICANN), 2018. - Makoto Yamada, Yuta Umezu, Kenji Fukumizu, Ichiro Takeuchi.
Post Selection Inference with Kernels.
In Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), 2018. - Jiyi Li, Yukino Baba, Hisashi Kashima.
Simultaneous Clustering and Ranking from Pairwise Comparisons.
In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI), pp.XX-XX, 2018. - Guoxi Zhang, Tomoharu Iwata, Hisashi Kashima.
On Reducing Dimensionality of Labeled Data Efficiently.
In Proceedings of the 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2018. - Takuya Kuwahara, Yukino Baba, Hisashi Kashima, Takeshi Kishikawa, Junichi Tsurumi, Tomoyuki Haga, Yoshihiro Ujiie, Takamitsu Sasaki, Hideki Matsushima.
Payload-based Statistical Intrusion Detection for In-vehicle Networks.
In Proceedings of the Australian Workshop on Machine Learning for Cyber-security (co-located with PAKDD 2018), 2018 - Ryusuke Takahama, Yukino Baba, Nobuyuki Shimizu, Sumio Fujita, Hisashi Kashima.
AdaFlock: Adaptive Feature Discovery for Human-in-the-loop Predictive Modeling.
In Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI), 2018. - Yukino Baba, Tomoumi Takase, Kyohei Atarashi, Satoshi Oyama, Hisashi Kashima.
Data Analysis Competition Platform for Educational Purposes: Lessons Learned and Future Challenges.
In Proceedings of the 8th Symposium on Educational Advances in Artificial Intelligence (EAAI), 2018. - Junpei Naito, Yukino Baba, Hisashi Kashima, Takenori Takaki, Takuya Funo.
Predictive Modeling of Learning Continuation in Preschool Education Using Temporal Patterns of Development Tests
In Proceedings of the 8th Symposium on Educational Advances in Artificial Intelligence (EAAI), 2018.
2017
Journal
- Sho Yokoi, Hiroshi Kajino, Hisashi Kashima.
Link Prediction in Sparse Networks by Incidence Matrix Factorization.
Journal of Information Processing, Vol.25, pp.477-485, 2017.
International Conference
- Koh Takeuchi, Hisashi Kashima, Naonori Ueda.
Autoregressive Tensor Factorization for Spatio-temporal Predictions.
In Proceedings of the 2017 IEEE International Conference on Data Mining (ICDM), 2017. - Jiyi Li, Yukino Baba, Hisashi Kashima.
Hyper Questions: Unsupervised Targeting of a Few Experts in Crowdsourcing.
In Proceeding of the 26th ACM International Conference on Information and Knowledge Management (CIKM), 2017. - Hirotaka Akita, Yukino Baba, Hisashi Kashima, Atsuto Seko.
Atomic Distance Kernel for Material Property Prediction.
In Proceeding of the 24th International Conference on Neural Information Processing (ICONIP), 2017. - Kosuke Yoshimura, Yukino Baba, Hisashi Kashima.
Quality Control for Crowdsourced Multi-Label Classification using RAkEL.
In Proceeding of the 24th International Conference on Neural Information Processing (ICONIP), 2017. - Jiyi Li, Tomohiro Arai, Yukino Baba, Hisashi Kashima, Shotaro Miwa.
Distributed Multi-task Learning for Sensor Network.
In Proceeding of the European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2017. - Guoxi Zhang, Tomoharu Iwata, Hisashi Kashima.
Robust Multi-view Topic Modeling by Incorporating Detecting Anomalies.
In Proceeding of the European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2017. - Koh Takeuchi, Yoshinobu Kawahara, Tomoharu Iwata.
Structurally Regularized Non-negative Tensor Factorization for Spatio-temporal Pattern Discoveries.
In Proceeding of the European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2017. - Yukihiro Tagami.
AnnexML: Approximate Nearest Neighbor Search for Extreme Multi-label Classification.
In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017. - Yukihiro Tagami.
Learning Extreme Multi-label Tree-classifier via Nearest Neighbor Graph Partitioning.
In the 26th International Conference on World Wide Web Companion (WWW), 2017. - Jiuding Duan, Jiyi Li, Yukino Baba, Hisashi Kashima.
A Generalized Model for Multidimensional Intransitivity.
In Proceedings of the 21st Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2017. - Takeru Sunahase, Yukino Baba, Hisashi Kashima.
Pairwise HITS: Quality Estimation from Pairwise Comparisons in Creator-Evaluator Crowdsourcing Process.
In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), 2017. - Nozomi Nori, Hisashi Kashima, Kazuto Yamashita, Susumu Kunisawa, Yuichi Imanaka.
Learning Implicit Tasks for Patient-Specific Risk Modeling in ICU.
In Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI), 2017. - Yuji Horiguchi, Yukino Baba, Hisashi Kashima, Masahito Suzuki, Hiroki Kayahara, Jun Maeno.
Predicting Fuel Consumption and Flight Delays for Low-cost Airlines.
In Proceedings of the 29th Conference on Innovative Applications of Artificial Intelligence (IAAI), 2017.
2016
Journal
- Satoshi Oyama, Yukino Baba, Ikki Ohmukai, Hiroaki Dokoshi, Hisashi Kashima.
Crowdsourcing Chart Digitizer: Task Design and Quality Control for Making Legacy Open Data Machine-Readable.
International Journal of Data Science and Analytics, 2016. - Yukino Baba, Kei Kinoshita, Hisashi Kashima.
Participation Recommendation System for Crowdsourcing Contests.
Expert Systems with Applications, Vol.58, pp.174–183, 2016. - Naoki Otani, Yukino Baba, Hisashi Kashima.
Quality Control of Crowdsourced Classication Using Hierarchical Class Structures.
Expert Systems with Applications, Vol.58, pp.155–163, 2016.
International Conference
- Kaito Fujii, Hisashi Kashima.
Budgeted Stream-based Active Learning via Adaptive Submodular Maximization.
In Advances in Neural Information Processing Systems (NIPS) 29, 2016. - Patrick Jörger, Yukino Baba, Hisashi Kashima.
Learning to Enumerate.
In Proceedings of the 25th International Conference on Artificial Neural Networks (ICANN), pp.453-460, Barcelona, Spain, 2016. - Sho Yokoi, Hiroshi Kajino, Hisashi Kashima.
Link Prediction by Incidence Matrix Factorisation.
In Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI), pp.1730-1731, The Hague, Holland, 2016. - Ryusuke Takahama, Toshihiro Kamishima, Hisashi Kashima.
Progressive Comparison for Ranking Estimation.
In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), pp.3882-3888, New York, NY, USA, 2016. - Yo Ehara, Yukino Baba, Masao Utiyama, Eiichiro Sumita.
Assessing Translation Ability through Vocabulary Ability Assessment.
In Proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI), pp.3712-3718, New York, NY, USA, 2016.
Others
2015
Journal
- Kai Morino, Yoshito Hirata, Ryota Tomioka, Hisashi Kashima, Kenji Yamanishi, Norihiro Hayashi, Shin Egawa, Kazuyuki Aihara.
Predicting Disease Progression from Short Biomarker Series Using Expert Advice Algorithm.
Scientific Reports, Vol.5, No.8953, doi:10.1038/srep08953, 2015. - Yasunobu Nohara, Eiko Kai, Partha Ghosh, Rafiqul Islam, Ashir Ahmed, Masahiro Kuroda, Sozo Inoue, Tatsuo Hiramatsu, Michio Kimura, Shuji Shimizu, Kunihisa Kobayashi, Yukino Baba, Hisashi Kashima, Koji Tsuda, Masashi Sugiyama, Mathieu Blondel, Naonori Ueda, Masaru Kitsuregawa, Naoki Nakashima.
A Health Checkup and Tele-Medical Intervention Program for Preventive Medicine in Developing Countries: A Verification Study.
Journal of Medical Internet Research (JMIR), Vol. 17, No. 1, 2015.
International Conference
- Naoki Otani, Yukino Baba, Hisashi Kashima.
Quality Control for Crowdsourced Hierarchical Classification.
In Proceedings of the 2015 IEEE International Conference on Data Mining (ICDM), pp.937-942, Atlantic City, NJ, USA, 2015. - Satoshi Oyama, Yukino Baba, Ikki Ohmukai, Hiroaki Dokoshi, Hisashi Kashima.
From One Star to Three Stars: Upgrading Legacy Open Data Using Crowdsourcing.
In Proceedings of the 2015 International Conference on Data Science and Advanced Analytics (DSAA), pp.1-9, Paris, France, 2015. - Junpei Komiyama, Junya Honda, Hisashi Kashima, Hiroshi Nakagawa.
Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem.
In Proceedings of the 28nd Annual Conference on Learning Theory (COLT), pp.1141-1154, Paris, France, 2015. - Jiuding Duan, Atsuto Seko, Hisashi Kashima.
Quantum Energy Prediction Using Graph Kernel.
In Proceedings of the 2015 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC), pp.1651-1656, Hong Kong, China, 2015. - Yukino Baba, Hisashi Kashima, Yasunobu Nohara, Eiko Kai, Partha Ghosh, Rafiqul Islam, Ashir Ahmed, Masahiro Kuroda, Sozo Inoue, Tatsuo Hiramatsu, Michio Kimura, Shuji Shimizu, Kunihisa Kobayashi, Koji Tsuda, Masashi Sugiyama, Mathieu Blondel, Naonori Ueda, Masaru Kitsuregawa, Naoki Nakashima.
Predictive Approaches for Low-cost Preventive Medicine Program in Developing Countries.
In Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp.1681-1690, Sydney, Australia, 2015. - Nozomi Nori, Hisashi Kashima, Kazuto Yamashita, Hiroshi Ikai, Yuichi Imanaka.
Simultaneous Modeling of Multiple Diseases for Mortality Prediction in Acute Hospital Care.
In Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) , pp.855-864, Sydney, Australia, 2015. - Shunsuke Kajimura, Yukino Baba, Hiroshi Kajino, Hisashi Kashima.
Quality Control for Crowdsourced POI Collection.
In Proceedings of the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp.255-267, Ho Chi Minh City, Vietnam, 2015. - Takuya Akiba, Takanori Hayashi, Nozomi Nori, Yoichi Iwata, Yuichi Yoshida.
Efficient Top-k Shortest-path Distance Queries on Large Networks by Pruned Landmark.
In Proceedings of the 29th National Conference on Artificial Intelligence (AAAI), pp.2-8, Austin Texas, USA, 2015. - Hisashi Kashima, Yukino Baba, Satoshi Oyama.
Tutorial: Crowdsourcing for Big Data Analytics.
In the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Ho Chi Minh City, Vietnam, 2015.
2014
Journal
- Hiroshi Kajino, Hiromi Arai, Hisashi Kashima.
Preserving Worker Privacy in Crowdsourcing.
Data Mining and Knowledge Discovery, Vol.27, No.5-6, pp.1314-1335, 2014. - Yukino Baba, Hisashi Kashima, Kei Kinoshita, Goushi Yamaguchi, Yosuke Akiyoshi.
Leveraging Non-expert Crowdsourcing Workers for Improper Task Detection in Crowdsourcing Marketplaces.
Expert Systems with Applications, Vol.41, No.6, pp.2678-2687, 2014.
International Conference
- Yukino Baba, Nozomi Nori, Shigeru Saito, Hisashi Kashima.
Crowdsourced Data Analytics: A Case Study of Predictive Modeling Competition.
In Proceedings of the 2014 International Conference on Data Science and Advanced Analytics (DSAA), pp.284-289, Shanghai, China, 2014. - Toshihiro Watanabe, Hisashi Kashima.
A Label Completion Approach to Crowd Approximation.
In Proceedings of the 21st International Conference on Neural Information Processing (ICONIP), pp.377-385, Kuching, Sarawak, Malaysia, 2014. - Ryoma Kawajiri, Masamichi Shimosaka, Hisashi Kashima.
Steered Crowdsensing: Incentive Design towards Quality-Oriented Place-Centric Crowdsensing.
In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), pp.691-701, Seattle, Washington, USA, 2014. - Hiroshi Kajino, Yukino Baba, Hisashi Kashima.
Instance-privacy Preserving Crowdsourcing.
In Proceedings of the 2nd Conference on Human Computation and Crowdsourcing (HCOMP), pp.96-103, Pittsburgh, USA, 2014. - Issei Sato, Hisashi Kashima, Hiroshi Nakagawa.
Latent Confusion Analysis by Normalized Gamma Construction.
In Proceedings of the 31st International Conference on Machine Learning (ICML), pp.1116-1124, Beijing, China, 2014.
Please see here for publications before March, 2014.