Kernels for Semi-Structured Data. - Hisashi Kashima; Teruo Koyanagi (ICML, 2002)

Mining Significant Pairs of Patterns from Graph Structures with Class Labels. - Akihiro Inokuchi; Hisashi Kashima (ICDM, 2003)

Marginalized Kernels Between Labeled Graphs. - Hisashi Kashima; Koji Tsuda; Akihiro Inokuchi (ICML, 2003)

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

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

Eigenspace-based anomaly detection in computer systems. - Tsuyoshi Idé; Hisashi Kashima (KDD, 2004)

Efficient filtering methods for clustering cDNAs with spliced sequence alignment. - Tetsuo Shibuya; Hisashi Kashima; Akihiko Konagaya (Bioinform., 2004)

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

A Parameterized Probabilistic Model of Network Evolution for Supervised Link Prediction. - Hisashi Kashima; Naoki Abe (ICDM, 2006)

Risk-Sensitive Learning via Expected Shortfall Minimization. - Hisashi Kashima (SDM, 2006)

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

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

Risk-Sensitive Learning via Minimization of Empirical Conditional Value-at-Risk. - Hisashi Kashima (IEICE Trans. Inf. Syst., 2007)

A Spectrum Tree Kernel. - Tetsuji Kuboyama; Kouichi Hirata; Hisashi Kashima; Kiyoko F. Aoki-Kinoshita; Hiroshi Yasuda (Inf. Media Technol., 2007)

Training Conditional Random Fields Using Incomplete Annotations. - Yuta Tsuboi; Hisashi Kashima; Shinsuke Mori; Hiroki Oda; Yuji Matsumoto 001 (COLING, 2008)

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

K-means clustering of proportional data using L1 distance. - Hisashi Kashima; Jianying Hu; Bonnie K. Ray; Moninder Singh (ICPR, 2008)

Regression with interval output values. - Hisashi Kashima; Kazutaka Yamasaki; Akihiro Inokuchi; Hiroto Saigo (ICPR, 2008)

A new objective function for sequence labeling. - Yuta Tsuboi; Hisashi Kashima (ICPR, 2008)

Unsupervised Change Analysis Using Supervised Learning. - Shohei Hido; Tsuyoshi Idé; Hisashi Kashima; Harunobu Kubo; Hirofumi Matsuzawa (PAKDD, 2008)

Roughly Balanced Bagging for Imbalanced Data. - Shohei Hido; Hisashi Kashima (SDM, 2008)

Integration of Multiple Networks for Robust Label Propagation. - Tsuyoshi Kato; Hisashi Kashima; Masashi Sugiyama (SDM, 2008)

Side Effect Prediction Using Cooperative Pathways. - Mutsumi Fukuzaki; Mio Seki; Hisashi Kashima; Jun Sese (BIBM, 2009)

A Linear-Time Graph Kernel. - Shohei Hido; Hisashi Kashima (ICDM, 2009)

Least absolute policy iteration for robust value function approximation. - Masashi Sugiyama; Hirotaka Hachiya; Hisashi Kashima; Tetsuro Morimura (ICRA, 2009)

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

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

Simultaneous inference of biological networks of multiple species from genome-wide data and evolutionary information: a semi-supervised approach. - Hisashi Kashima; Yoshihiro Yamanishi; Tsuyoshi Kato; Masashi Sugiyama; Koji Tsuda (Bioinform., 2009)

Recent Advances and Trends in Large-Scale Kernel Methods. - Hisashi Kashima; Tsuyoshi Idé; Tsuyoshi Kato; Masashi Sugiyama (IEICE Trans. Inf. Syst., 2009)

Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation. - Yuta Tsuboi; Hisashi Kashima; Shohei Hido; Steffen Bickel; Masashi Sugiyama (J. Inf. Process., 2009)

Roughly balanced bagging for imbalanced data. - Shohei Hido; Hisashi Kashima; Yutaka Takahashi 001 (Stat. Anal. Data Min., 2009)

Robust Label Propagation on Multiple Networks. - Tsuyoshi Kato; Hisashi Kashima; Masashi Sugiyama (IEEE Trans. Neural Networks, 2009)

Averaged Stochastic Gradient Descent with Feedback: An Accurate, Robust, and Fast Training Method. - Xu Sun 001; Hisashi Kashima; Takuya Matsuzaki; Naonori Ueda (ICDM, 2010)

Nonparametric Return Distribution Approximation for Reinforcement Learning. - Tetsuro Morimura; Masashi Sugiyama; Hisashi Kashima; Hirotaka Hachiya; Toshiyuki Tanaka (ICML, 2010)

A Fast Augmented Lagrangian Algorithm for Learning Low-Rank Matrices. - Ryota Tomioka; Taiji Suzuki; Masashi Sugiyama; Hisashi Kashima (ICML, 2010)

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

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

Parametric Return Density Estimation for Reinforcement Learning. - Tetsuro Morimura; Masashi Sugiyama; Hisashi Kashima; Hirotaka Hachiya; Toshiyuki Tanaka (UAI, 2010)

Protein complex prediction via verifying and reconstructing the topology of domain-domain interactions. - Yosuke Ozawa; Rintaro Saito; Shigeo Fujimori; Hisashi Kashima; Masamichi Ishizaka; Hiroshi Yanagawa; Etsuko Miyamoto-Sato; Masaru Tomita (BMC Bioinform., 2010)

Reaction graph kernels predict EC numbers of unknown enzymatic reactions in plant secondary metabolism. - Hiroto Saigo; Masahiro Hattori; Hisashi Kashima; Koji Tsuda (BMC Bioinform., 2010)

Cartesian Kernel: An Efficient Alternative to the Pairwise Kernel. - Hisashi Kashima; Satoshi Oyama; Yoshihiro Yamanishi; Koji Tsuda (IEICE Trans. Inf. Syst., 2010)

Least Absolute Policy Iteration-A Robust Approach to Value Function Approximation. - Masashi Sugiyama; Hirotaka Hachiya; Hisashi Kashima; Tetsuro Morimura (IEICE Trans. Inf. Syst., 2010)

A Transfer Learning Approach and Selective Integration of Multiple Types of Assays for Biological Network Inference. - Tsuyoshi Kato; Kinya Okada; Hisashi Kashima; Masashi Sugiyama (Int. J. Knowl. Discov. Bioinform., 2010)

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

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

Cross-Temporal Link Prediction. - Satoshi Oyama; Kohei Hayashi; Hisashi Kashima (ICDM, 2011)

A New Multi-task Learning Method for Personalized Activity Recognition. - Xu Sun 001; Hisashi Kashima; Ryota Tomioka; Naonori Ueda; Ping Li 001 (ICDM, 2011)

Statistical Performance of Convex Tensor Decomposition. - Ryota Tomioka; Taiji Suzuki; Kohei Hayashi; Hisashi Kashima (NIPS, 2011)

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

Large Scale Real-Life Action Recognition Using Conditional Random Fields with Stochastic Training. - Xu Sun 001; Hisashi Kashima; Ryota Tomioka; Naonori Ueda (PAKDD (2), 2011)

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

A Convex Formulation for Learning from Crowds. - Hiroshi Kajino; Yuta Tsuboi; Hisashi Kashima (AAAI, 2012)

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

Learning from Crowds and Experts. - Hiroshi Kajino; Yuta Tsuboi; Issei Sato; Hisashi Kashima (HCOMP@AAAI, 2012)

Generalized Expansion Dimension. - Michael E. Houle; Hisashi Kashima; Michael Nett (ICDM Workshops, 2012)

Fast Computation of Subpath Kernel for Trees. - Daisuke Kimura; Hisashi Kashima (ICML, 2012)

Hash-based structural similarity for semi-supervised Learning on attribute graphs. - Shohei Hido; Hisashi Kashima (ICPR, 2012)

Fast Similarity Computation in Factorized Tensors. - Michael E. Houle; Hisashi Kashima; Michael Nett (SISAP, 2012)

Tensor factorization using auxiliary information. - Atsuhiro Narita; Kohei Hayashi; Ryota Tomioka; Hisashi Kashima (Data Min. Knowl. Discov., 2012)

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

Link Prediction Across Time via Cross-Temporal Locality Preserving Projections. - Satoshi Oyama; Kohei Hayashi; Hisashi Kashima (IEICE Trans. Inf. Syst., 2012)

Self-measuring Similarity for Multi-task Gaussian Process. - Kohei Hayashi; Takashi Takenouchi; Ryota Tomioka; Hisashi Kashima (ICML Unsupervised and Transfer Learning, 2012)

Clustering Crowds. - Hiroshi Kajino; Yuta Tsuboi; Hisashi Kashima (AAAI, 2013)

Crowdsourcing Quality Control for Item Ordering Tasks. - Toshiko Matsui; Yukino Baba; Toshihiro Kamishima; Hisashi Kashima (HCOMP (Works in Progress / Demos), 2013)

EM-Based Inference of True Labels Using Confidence Judgments. - Satoshi Oyama; Yukino Baba; Yuko Sakurai; Hisashi Kashima (HCOMP (Works in Progress / Demos), 2013)

Leveraging Crowdsourcing to Detect Improper Tasks in Crowdsourcing Marketplaces. - Yukino Baba; Hisashi Kashima; Kei Kinoshita; Goushi Yamaguchi; Yosuke Akiyoshi (IAAI, 2013)

Accurate Integration of Crowdsourced Labels Using Workers' Self-reported Confidence Scores. - Satoshi Oyama; Yukino Baba; Yuko Sakurai; Hisashi Kashima (IJCAI, 2013)

Statistical quality estimation for general crowdsourcing tasks. - Yukino Baba; Hisashi Kashima (KDD, 2013)

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

Fast Iterative Mining Using Sparsity-Inducing Loss Functions. - Hiroto Saigo; Hisashi Kashima; Koji Tsuda (IEICE Trans. Inf. Syst., 2013)

Large-Scale Personalized Human Activity Recognition Using Online Multitask Learning. - Xu Sun 001; Hisashi Kashima; Naonori Ueda (IEEE Trans. Knowl. Data Eng., 2013)

Crowdsourced data analytics: A case study of a predictive modeling competition. - Yukino Baba; Nozomi Nori; Shigeru Saito; Hisashi Kashima (DSAA, 2014)

Quality Control for Crowdsourced Enumeration Tasks. - Shunsuke Kajimura; Yukino Baba; Hiroshi Kajino; Hisashi Kashima (HCOMP, 2014)

Instance-Privacy Preserving Crowdsourcing. - Hiroshi Kajino; Yukino Baba; Hisashi Kashima (HCOMP, 2014)

Steered crowdsensing: incentive design towards quality-oriented place-centric crowdsensing. - Ryoma Kawajiri; Masamichi Shimosaka; Hisashi Kashima (UbiComp, 2014)

Latent Confusion Analysis by Normalized Gamma Construction. - Issei Sato; Hisashi Kashima; Hiroshi Nakagawa (ICML, 2014)

A Label Completion Approach to Crowd Approximation. - Toshihiro Watanabe; Hisashi Kashima (ICONIP (2), 2014)

Learning an accurate entity resolution model from crowdsourced labels. - Jingjing Wang; Satoshi Oyama; Masahito Kurihara; Hisashi Kashima (ICUIMC, 2014)

Crowdordering. - Toshiko Matsui; Yukino Baba; Toshihiro Kamishima; Hisashi Kashima (PAKDD (2), 2014)

Preserving worker privacy in crowdsourcing. - Hiroshi Kajino; Hiromi Arai; Hisashi Kashima (Data Min. Knowl. Discov., 2014)

Leveraging non-expert crowdsourcing workers for improper task detection in crowdsourcing marketplaces. - Yukino Baba; Hisashi Kashima; Kei Kinoshita; Goushi Yamaguchi; Yosuke Akiyoshi (Expert Syst. Appl., 2014)

Regret Lower Bound and Optimal Algorithm in Dueling Bandit Problem. - Junpei Komiyama; Junya Honda; Hisashi Kashima; Hiroshi Nakagawa (COLT, 2015)

From one star to three stars: Upgrading legacy open data using crowdsourcing. - Satoshi Oyama; Yukino Baba; Ikki Ohmukai; Hiroaki Dokoshi; Hisashi Kashima (DSAA, 2015)

Quality Control for Crowdsourced Hierarchical Classification. - Naoki Otani; Yukino Baba; Hisashi Kashima (ICDM, 2015)

Predictive Approaches for Low-Cost Preventive Medicine Program in Developing Countries. - 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; et al. (KDD, 2015)

Simultaneous Modeling of Multiple Diseases for Mortality Prediction in Acute Hospital Care. - Nozomi Nori; Hisashi Kashima; Kazuto Yamashita; Hiroshi Ikai; Yuichi Imanaka (KDD, 2015)

Quality Control for Crowdsourced POI Collection. - Shunsuke Kajimura; Yukino Baba; Hiroshi Kajino; Hisashi Kashima (PAKDD (2), 2015)

Quantum Energy Prediction Using Graph Kernel. - Jiuding Duan; Atsuto Seko; Hisashi Kashima (SMC, 2015)

Link Prediction by Incidence Matrix Factorization. - Sho Yokoi; Hiroshi Kajino; Hisashi Kashima (ECAI, 2016)

Learning to Enumerate. - Patrick Jörger; Yukino Baba; Hisashi Kashima (ICANN (1), 2016)

Progressive Comparison for Ranking Estimation. - Ryusuke Takahama; Toshihiro Kamishima; Hisashi Kashima (IJCAI, 2016)

Budgeted stream-based active learning via adaptive submodular maximization. - Kaito Fujii; Hisashi Kashima (NIPS, 2016)

Participation recommendation system for crowdsourcing contests. - Yukino Baba; Kei Kinoshita; Hisashi Kashima (Expert Syst. Appl., 2016)

Quality control of crowdsourced classification using hierarchical class structures. - Naoki Otani; Yukino Baba; Hisashi Kashima (Expert Syst. Appl., 2016)

Crowdsourcing chart digitizer: task design and quality control for making legacy open data machine-readable. - Satoshi Oyama; Yukino Baba; Ikki Ohmukai; Hiroaki Dokoshi; Hisashi Kashima (Int. J. Data Sci. Anal., 2016)

Predicting Fuel Consumption and Flight Delays for Low-Cost Airlines. - Yuji Horiguchi; Yukino Baba; Hisashi Kashima; Masahito Suzuki; Hiroki Kayahara; Jun Maeno (AAAI, 2017)

Learning Implicit Tasks for Patient-Specific Risk Modeling in ICU. - Nozomi Nori; Hisashi Kashima; Kazuto Yamashita; Susumu Kunisawa; Yuichi Imanaka (AAAI, 2017)

Pairwise HITS: Quality Estimation from Pairwise Comparisons in Creator-Evaluator Crowdsourcing Process. - Takeru Sunahase; Yukino Baba; Hisashi Kashima (AAAI, 2017)

Hyper Questions: Unsupervised Targeting of a Few Experts in Crowdsourcing. - Jiyi Li; Yukino Baba; Hisashi Kashima (CIKM, 2017)

Using Posters to Recommend Anime and Mangas in a Cold-Start Scenario. - Jill-Jênn Vie; Florian Yger; Ryan Lahfa; Basile Clement; Kévin Cocchi; Thomas Chalumeau; Hisashi Kashima (MANPU@ICDAR, 2017)

Autoregressive Tensor Factorization for Spatio-Temporal Predictions. - Koh Takeuchi 001; Hisashi Kashima; Naonori Ueda (ICDM, 2017)

Atomic Distance Kernel for Material Property Prediction. - Hirotaka Akita; Yukino Baba; Hisashi Kashima; Atsuto Seko (ICONIP (1), 2017)

Quality Control for Crowdsourced Multi-label Classification Using RAkEL. - Kosuke Yoshimura; Yukino Baba; Hisashi Kashima (ICONIP (1), 2017)

A Generalized Model for Multidimensional Intransitivity. - Jiuding Duan; Jiyi Li; Yukino Baba; Hisashi Kashima (PAKDD (2), 2017)

Distributed Multi-task Learning for Sensor Network. - Jiyi Li; Tomohiro Arai; Yukino Baba; Hisashi Kashima; Shotaro Miwa (ECML/PKDD (2), 2017)

Robust Multi-view Topic Modeling by Incorporating Detecting Anomalies. - Guoxi Zhang; Tomoharu Iwata; Hisashi Kashima (ECML/PKDD (2), 2017)

Iterative Reduction Worker Filtering for Crowdsourced Label Aggregation. - Jiyi Li; Hisashi Kashima (WISE (2), 2017)

Link Prediction in Sparse Networks by Incidence Matrix Factorization. - Sho Yokoi; Hiroshi Kajino; Hisashi Kashima (J. Inf. Process., 2017)

Data Analysis Competition Platform for Educational Purposes: Lessons Learned and Future Challenges. - Yukino Baba; Tomoumi Takase; Kyohei Atarashi; Satoshi Oyama; Hisashi Kashima (AAAI, 2018)

Predictive Modeling of Learning Continuation in Preschool Education Using Temporal Patterns of Development Tests. - Junpei Naito; Yukino Baba; Hisashi Kashima; Takenori Takaki; Takuya Funo (AAAI, 2018)

AdaFlock: Adaptive Feature Discovery for Human-in-the-loop Predictive Modeling. - Ryusuke Takahama; Yukino Baba; Nobuyuki Shimizu; Sumio Fujita; Hisashi Kashima (AAAI, 2018)

Incorporating Worker Similarity for Label Aggregation in Crowdsourcing. - Jiyi Li; Yukino Baba; Hisashi Kashima (ICANN (2), 2018)

Short-Term Precipitation Prediction with Skip-Connected PredNet. - Ryoma Sato; Hisashi Kashima; Takehiro Yamamoto (ICANN (3), 2018)

BayesGrad: Explaining Predictions of Graph Convolutional Networks. - Hirotaka Akita; Kosuke Nakago; Tomoki Komatsu; Yohei Sugawara; Shin-ichi Maeda; Yukino Baba; Hisashi Kashima (ICONIP (5), 2018)

Simultaneous Clustering and Ranking from Pairwise Comparisons. - Jiyi Li; Yukino Baba; Hisashi Kashima (IJCAI, 2018)

Payload-Based Statistical Intrusion Detection for In-Vehicle Networks. - Takuya Kuwahara; Yukino Baba; Hisashi Kashima; Takeshi Kishikawa; Jun'ichi Tsurumi; Tomoyuki Haga; Yoshihiro Ujiie; Takamitsu Sasaki; Hideki Matsushima (PAKDD (Workshops), 2018)

On Reducing Dimensionality of Labeled Data Efficiently. - Guoxi Zhang; Tomoharu Iwata; Hisashi Kashima (PAKDD (3), 2018)

Dual Convolutional Neural Network for Graph of Graphs Link Prediction. - Shonosuke Harada; Hirotaka Akita; Masashi Tsubaki; Yukino Baba; Ichigaku Takigawa; Yoshihiro Yamanishi; Hisashi Kashima (CoRR, 2018)

Supervised and Unsupervised Intrusion Detection Based on CAN Message Frequencies for In-vehicle Network. - Takuya Kuwahara; Yukino Baba; Hisashi Kashima; Takeshi Kishikawa; Jun'ichi Tsurumi; Tomoyuki Haga; Yoshihiro Ujiie; Takamitsu Sasaki; Hideki Matsushima (J. Inf. Process., 2018)

Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing. - Jill-Jênn Vie; Hisashi Kashima (AAAI, 2019)

Active Change-Point Detection. - Shogo Hayashi; Yoshinobu Kawahara; Hisashi Kashima (ACML, 2019)

Learning to Sample Hard Instances for Graph Algorithms. - Ryoma Sato; Makoto Yamada; Hisashi Kashima (ACML, 2019)

Probabilistic Modeling of Peer Correction and Peer Assessment. - Takeru Sunahase; Yukino Baba; Hisashi Kashima (EDM, 2019)

Interdependence Model for Multi-label Classification. - Kosuke Yoshimura; Tomoaki Iwase; Yukino Baba; Hisashi Kashima (ICANN (4), 2019)

Crownn: Human-in-the-loop Network with Crowd-generated Inputs. - Yusuke Sakata; Yukino Baba; Hisashi Kashima (ICASSP, 2019)

Long-Term Prediction of Small Time-Series Data Using Generalized Distillation. - Shogo Hayashi; Akira Tanimoto; Hisashi Kashima (IJCNN, 2019)

In-Vehicle Network Intrusion Detection and Explanation Using Density Ratio Estimation. - Daiki Tanaka; Makoto Yamada; Hisashi Kashima; Takeshi Kishikawa; Tomoyuki Haga; Takamitsu Sasaki (ITSC, 2019)

Fast Sparse Group Lasso. - Yasutoshi Ida; Yasuhiro Fujiwara; Hisashi Kashima (NeurIPS, 2019)

Theoretical evidence for adversarial robustness through randomization. - Rafael Pinot; Laurent Meunier; Alexandre Araujo; Hisashi Kashima; Florian Yger; Cédric Gouy-Pailler; Jamal Atif (NeurIPS, 2019)

Approximation Ratios of Graph Neural Networks for Combinatorial Problems. - Ryoma Sato; Makoto Yamada; Hisashi Kashima (NeurIPS, 2019)

Context-Regularized Neural Collaborative Filtering for Game App Recommendation. - Shonosuke Harada; Kazuki Taniguchi; Makoto Yamada; Hisashi Kashima (RecSys (Late-Breaking Results), 2019)

Large-scale Driver Identification Using Automobile Driving Data. - Daiki Tanaka; Yukino Baba; Hisashi Kashima; Yuta Okubo (SMC, 2019)

Theoretical evidence for adversarial robustness through randomization: the case of the Exponential family. - Rafael Pinot; Laurent Meunier; Alexandre Araujo; Hisashi Kashima; Florian Yger; Cédric Gouy-Pailler; Jamal Atif (CoRR, 2019)

Learning to Find Hard Instances of Graph Problems. - Ryoma Sato; Makoto Yamada; Hisashi Kashima (CoRR, 2019)

Stress Prediction from Head Motion. - Hitoshi Kusano; Yuji Horiguchi; Yukino Baba; Hisashi Kashima (DSAA, 2020)

Simultaneous Link Prediction on Unaligned Networks Using Graph Embedding and Optimal Transport. - Luu Huu Phuc; Koh Takeuchi 001; Makoto Yamada; Hisashi Kashima (DSAA, 2020)

Topological Bayesian Optimization with Persistence Diagrams. - Tatsuya Shiraishi; Tam Le; Hisashi Kashima; Makoto Yamada (ECAI, 2020)

CrowDEA: Multi-View Idea Prioritization with Crowds. - Yukino Baba; Jiyi Li; Hisashi Kashima (HCOMP, 2020)

Fast Deterministic CUR Matrix Decomposition with Accuracy Assurance. - Yasutoshi Ida; Sekitoshi Kanai; Yasuhiro Fujiwara; Tomoharu Iwata; Koh Takeuchi 001; Hisashi Kashima (ICML, 2020)

An Intransitivity Model for Matchup and Pairwise Comparison. - Yan Gu; Jiuding Duan; Hisashi Kashima (ICPR, 2020)

Performance as a Constraint: An Improved Wisdom of Crowds Using Performance Regularization. - Jiyi Li; Yasushi Kawase; Yukino Baba; Hisashi Kashima (IJCAI, 2020)

Fast Unbalanced Optimal Transport on a Tree. - Ryoma Sato; Makoto Yamada; Hisashi Kashima (NeurIPS, 2020)

Counterfactual Propagation for Semi-supervised Individual Treatment Effect Estimation. - Shonosuke Harada; Hisashi Kashima (ECML/PKDD (1), 2020)

Fast and Robust Comparison of Probability Measures in Heterogeneous Spaces. - Ryoma Sato; Marco Cuturi; Makoto Yamada; Hisashi Kashima (CoRR, 2020)

Chemical Property Prediction Under Experimental Biases. - Yang Liu; Hisashi Kashima (CoRR, 2020)

Synthetic accessibility assessment using auxiliary responses. - Shun Ito; Yukino Baba; Tetsu Isomura; Hisashi Kashima (Expert Syst. Appl., 2020)

Dual graph convolutional neural network for predicting chemical networks. - Shonosuke Harada; Hirotaka Akita; Masashi Tsubaki; Yukino Baba; Ichigaku Takigawa; Yoshihiro Yamanishi; Hisashi Kashima (BMC Bioinform., 2020)

Learning Individually Fair Classifier with Path-Specific Causal-Effect Constraint. - Yoichi Chikahara; Shinsaku Sakaue; Akinori Fujino; Hisashi Kashima (AISTATS, 2021)

Regret Minimization for Causal Inference on Large Treatment Space. - Akira Tanimoto; Tomoya Sakai 001; Takashi Takenouchi; Hisashi Kashima (AISTATS, 2021)

Grab the Reins of Crowds: Estimating the Effects of Crowd Movement Guidance Using Causal Inference. - Koh Takeuchi 001; Ryo Nishida; Hisashi Kashima; Masaki Onishi (AAMAS, 2021)

Preliminary Experiments to Examine the Stability of Bias-Aware Techniques. - Toshihiro Kamishima; Shotaro Akaho; Yukino Baba; Hisashi Kashima (BIAS, 2021)

GraphITE: Estimating Individual Effects of Graph-structured Treatments. - Shonosuke Harada; Hisashi Kashima (CIKM, 2021)

Computationally Efficient Wasserstein Loss for Structured Labels. - Ayato Toyokuni; Sho Yokoi; Hisashi Kashima; Makoto Yamada (EACL (Student Research Workshop), 2021)

Label Aggregation for Crowdsourced Triplet Similarity Comparisons. - Jiyi Li; Lucas Ryo Endo; Hisashi Kashima (ICONIP (6), 2021)

In-Vehicle Network Attack Detection Across Vehicle Models: A Supervised-Unsupervised Hybrid Approach. - Shu Nakamura; Koh Takeuchi 001; Hisashi Kashima; Takeshi Kishikawa; Takashi Ushio; Tomoyuki Haga; Takamitsu Sasaki (ITSC, 2021)

Dynamic Hawkes Processes for Discovering Time-evolving Communities' States behind Diffusion Processes. - Maya Okawa; Tomoharu Iwata; Yusuke Tanaka 002; Hiroyuki Toda; Takeshi Kurashima; Hisashi Kashima (KDD, 2021)

Causal Combinatorial Factorization Machines for Set-Wise Recommendation. - Akira Tanimoto; Tomoya Sakai 001; Takashi Takenouchi; Hisashi Kashima (PAKDD (2), 2021)

Crowdsourcing Evaluation of Saliency-Based XAI Methods. - Xiaotian Lu; Arseny Tolmachev; Tatsuya Yamamoto; Koh Takeuchi 001; Seiji Okajima; Tomoyoshi Takebayashi; Koji Maruhashi; Hisashi Kashima (ECML/PKDD (5), 2021)

Inter-domain Multi-relational Link Prediction. - Luu Huu Phuc; Koh Takeuchi 001; Seiji Okajima; Arseny Tolmachev; Tomoyoshi Takebayashi; Koji Maruhashi; Hisashi Kashima (ECML/PKDD (2), 2021)

Random Features Strengthen Graph Neural Networks. - Ryoma Sato; Makoto Yamada; Hisashi Kashima (SDM, 2021)

Learning to Rank for Multi-Step Ahead Time-Series Forecasting. - Jiuding Duan; Hisashi Kashima (IEEE Access, 2021)

Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations. - Sein Minn; Jill-Jênn Vie; Koh Takeuchi 001; Hisashi Kashima; Feida Zhu 001 (AAAI, 2022)

Variational Factorization Machines for Preference Elicitation in Large-Scale Recommender Systems. - Jill-Jênn Vie; Tomas Rigaux; Hisashi Kashima (IEEE Big Data, 2022)

Twin Papers: A Simple Framework of Causal Inference for Citations via Coupling. - Ryoma Sato; Makoto Yamada; Hisashi Kashima (CIKM, 2022)

Improving Pairwise Rank Aggregation via Querying for Rank Difference. - Guoxi Zhang; Jiyi Li; Hisashi Kashima (DSAA, 2022)

Learning Evolvable Time-series Shapelets. - Akihiro Yamaguchi; Ken Ueno; Hisashi Kashima (ICDE, 2022)

Re-evaluating Word Mover's Distance. - Ryoma Sato; Makoto Yamada; Hisashi Kashima (ICML, 2022)

Mitigating Observation Biases in Crowdsourced Label Aggregation. - Ryosuke Ueda; Koh Takeuchi 001; Hisashi Kashima (ICPR, 2022)

Learning Optimal Priors for Task-Invariant Representations in Variational Autoencoders. - Hiroshi Takahashi; Tomoharu Iwata; Atsutoshi Kumagai; Sekitoshi Kanai; Masanori Yamada; Yuki Yamanaka; Hisashi Kashima (KDD, 2022)

Batch Reinforcement Learning from Crowds. - Guoxi Zhang; Hisashi Kashima (ECML/PKDD (4), 2022)

Learning Time-series Shapelets Enhancing Discriminability. - Akihiro Yamaguchi; Ken Ueno; Hisashi Kashima (SDM, 2022)

Feature selection for discovering distributional treatment effect modifiers. - Yoichi Chikahara; Makoto Yamada; Hisashi Kashima (UAI, 2022)

Improving imbalanced classification using near-miss instances. - Akira Tanimoto; So Yamada; Takashi Takenouchi; Masashi Sugiyama; Hisashi Kashima (Expert Syst. Appl., 2022)

Poincare: Recommending Publication Venues via Treatment Effect Estimation. - Ryoma Sato; Makoto Yamada; Hisashi Kashima (J. Informetrics, 2022)

Bayesian optimization with partially specified queries. - Shogo Hayashi; Junya Honda; Hisashi Kashima (Mach. Learn., 2022)

Context-aware spatio-temporal event prediction via convolutional Hawkes processes. - Maya Okawa; Tomoharu Iwata; Yusuke Tanaka 002; Takeshi Kurashima; Hiroyuki Toda; Hisashi Kashima (Mach. Learn., 2022)

Constant Time Graph Neural Networks. - Ryoma Sato; Makoto Yamada; Hisashi Kashima (ACM Trans. Knowl. Discov. Data, 2022)

Behavior Estimation from Multi-Source Data for Offline Reinforcement Learning. - Guoxi Zhang; Hisashi Kashima (AAAI, 2023)

Mitigating Voter Attribute Bias for Fair Opinion Aggregation. - Ryosuke Ueda; Koh Takeuchi 001; Hisashi Kashima (AIES, 2023)

Time-series Shapelets with Learnable Lengths. - Akihiro Yamaguchi; Ken Ueno; Hisashi Kashima (CIKM, 2023)

Deep Knowledge Tracing is an implicit dynamic multidimensional item response theory model. - Jill-Jênn Vie; Hisashi Kashima (ICCE, 2023)

Label Selection Approach to Learning from Crowds. - Kosuke Yoshimura; Hisashi Kashima (ICONIP (8), 2023)

QTNet: Theory-based Queue Length Prediction for Urban Traffic. - Ryu Shirakami; Toshiya Kitahara; Koh Takeuchi 001; Hisashi Kashima (KDD, 2023)

Causal Effect Estimation on Hierarchical Spatial Graph Data. - Koh Takeuchi 001; Ryo Nishida; Hisashi Kashima; Masaki Onishi (KDD, 2023)

Regularizing Neural Networks with Meta-Learning Generative Models. - Shin'ya Yamaguchi; Daiki Chijiwa; Sekitoshi Kanai; Atsutoshi Kumagai; Hisashi Kashima (NeurIPS, 2023)

Estimating Treatment Effects Under Heterogeneous Interference. - Xiaofeng Lin 001; Guoxi Zhang; Xiaotian Lu; Han Bao 002; Koh Takeuchi 001; Hisashi Kashima (ECML/PKDD (1), 2023)

Multiview Representation Learning from Crowdsourced Triplet Comparisons. - Xiaotian Lu; Jiyi Li; Koh Takeuchi 001; Hisashi Kashima (WWW, 2023)

Making individually fair predictions with causal pathways. - Yoichi Chikahara; Shinsaku Sakaue; Akinori Fujino; Hisashi Kashima (Data Min. Knowl. Discov., 2023)

Learning Counterfactual Explanations with Intervals for Time-series Classification. - Akihiro Yamaguchi; Ken Ueno; Ryusei Shingaki; Hisashi Kashima (CIKM, 2024)

Evaluating Saliency Explanations in NLP by Crowdsourcing. - Xiaotian Lu; Jiyi Li; Zhen Wan; Xiaofeng Lin 001; Koh Takeuchi 001; Hisashi Kashima (LREC/COLING, 2024)

Understanding and Improving Source-Free Domain Adaptation from a Theoretical Perspective. - Yu Mitsuzumi; Akisato Kimura; Hisashi Kashima (CVPR, 2024)

AHP-Powered LLM Reasoning for Multi-Criteria Evaluation of Open-Ended Responses. - Xiaotian Lu; Jiyi Li; Koh Takeuchi 001; Hisashi Kashima (EMNLP (Findings), 2024)

Enhancing Chess Reinforcement Learning with Graph Representation. - Tomas Rigaux; Hisashi Kashima (NeurIPS, 2024)

Treatment Effect Estimation Under Unknown Interference. - Xiaofeng Lin 001; Guoxi Zhang; Xiaotian Lu; Hisashi Kashima (PAKDD (2), 2024)

Recovering Population Dynamics from a Single Point Cloud Snapshot. - Yuki Wakai; Koh Takeuchi 001; Hisashi Kashima (PAKDD (3), 2024)

Efficient Preference Elicitation in Iterative Combinatorial Auctions with Many Participants. - Ryota Maruo; Hisashi Kashima (PRIMA, 2024)

Online Policy Learning from Offline Preferences. - Guoxi Zhang; Han Bao 002; Hisashi Kashima (CoRR, 2024)

Mitigating Cognitive Biases in Multi-Criteria Crowd Assessment. - Shun Ito; Hisashi Kashima (CoRR, 2024)

Learning Neural Strategy-Proof Matching Mechanism from Examples. - Ryota Maruo; Koh Takeuchi 001; Hisashi Kashima (CoRR, 2024)

Neural Double Auction Mechanism. - Tsuyoshi Suehara; Koh Takeuchi 001; Hisashi Kashima; Satoshi Oyama; Yuko Sakurai; Makoto Yokoo (CoRR, 2024)

InfoCEVAE: treatment effect estimation with hidden confounding variables matching. - Shonosuke Harada; Hisashi Kashima (Mach. Learn., 2024)

Learning state importance for preference-based reinforcement learning. - Guoxi Zhang; Hisashi Kashima (Mach. Learn., 2024)

Trustworthy human computation: a survey. - Hisashi Kashima; Satoshi Oyama; Hiromi Arai; Junichiro Mori (Artif. Intell. Rev., 2024)

Learning Fair and Preferable Allocations through Neural Network. - Ryota Maruo; Koh Takeuchi 001; Hisashi Kashima (AAMAS, 2025)

Treatment Effect Estimation for Graph-Structured Targets. - Shonosuke Harada; Ryosuke Yoneda; Hisashi Kashima (PAKDD (6), 2025)

Cognitive Biases in Large Language Models: A Survey and Mitigation Experiments. - Yasuaki Sumita; Koh Takeuchi 001; Hisashi Kashima (SAC, 2025)

Federated Source-Free Domain Adaptation for Classification: Weighted Cluster Aggregation for Unlabeled Data. - Junki Mori; Kosuke Kihara; Taiki Miyagawa; Akinori F. Ebihara; Isamu Teranishi; Hisashi Kashima (WACV, 2025)

Scalable individual treatment effect estimator for large graphs. - Xiaofeng Lin 001; Han Bao 002; Yan Cui 008; Koh Takeuchi 001; Hisashi Kashima (Mach. Learn., 2025)

Emulating Retrieval Augmented Generation via Prompt Engineering for Enhanced Long Context Comprehension in LLMs. - Joon Park; Kyohei Atarashi; Koh Takeuchi 001; Hisashi Kashima (CoRR, 2025)

Exploring Causes and Mitigation of Hallucinations in Large Vision Language Models. - Yaqi Sun; Kyohei Atarashi; Koh Takeuchi 001; Hisashi Kashima (CoRR, 2025)

Dynamic Feature Selection from Variable Feature Sets Using Features of Features. - Katsumi Takahashi; Koh Takeuchi 001; Hisashi Kashima (CoRR, 2025)

Transfer learning with pre-trained conditional generative models. - Shin'ya Yamaguchi; Sekitoshi Kanai; Atsutoshi Kumagai; Daiki Chijiwa; Hisashi Kashima (Mach. Learn., 2025)

Learning Location-Guided Time-Series Shapelets. - Akihiro Yamaguchi; Ken Ueno; Hisashi Kashima (IEEE Trans. Knowl. Data Eng., 2025)

XicorAttention: Time Series Transformer Using Attention with Nonlinear Correlation. - Daichi Kimura; Tomonori Izumitani; Hisashi Kashima (CoRR, 2025)

Box-Constrained Softmax Function and Its Application for Post-Hoc Calibration. - Kyohei Atarashi; Satoshi Oyama; Hiromi Arai; Hisashi Kashima (CoRR, 2025)

Counterfactual Evaluation for Blind Attack Detection in LLM-based Evaluation Systems. - Lijia Liu; Takumi Kondo; Kyohei Atarashi; Koh Takeuchi 001; Jiyi Li; Shigeru Saito; Hisashi Kashima (CoRR, 2025)

Hierarchical Text Classification Using Black Box Large Language Models. - Kosuke Yoshimura; Hisashi Kashima (CoRR, 2025)

Unpacking the Implicit Norm Dynamics of Sharpness-Aware Minimization in Tensorized Models. - Tianxiao Cao; Kyohei Atarashi; Hisashi Kashima (CoRR, 2025)