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Hisashi Kashima

Hisashi Kashima

D-Index & Metrics

Computer Science

D-Index
44
Citations
9411
World Ranking
7504
National Ranking
104

Overview

Hisashi Kashima is affiliated with Kyoto University in Japan and conducts research primarily in the field of Computer Science, with a focus on Artificial Intelligence. The research spans several subfields including Statistics and Probability, Computer Science Applications, Computer Vision and Pattern Recognition, and Management Science and Operations Research.

The scientist's work encompasses multiple main topics such as:

  • Advanced Causal Inference Techniques
  • Mobile Crowdsensing and Crowdsourcing
  • Statistical Methods and Inference
  • Data Stream Mining Techniques
  • Anomaly Detection Techniques and Applications
  • Explainable Artificial Intelligence (XAI)
  • Computational Drug Discovery Methods

Kashima has authored publications in various venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • Transactions of the Japanese Society for Artificial Intelligence
  • Machine Learning
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Scientific Reports

Recent notable papers feature the following titles, years, and publication venues:

  • "A Convex Formulation for Learning from Crowds", 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Dual graph convolutional neural network for predicting chemical networks", 2020, BMC Bioinformatics
  • "Interpretable Knowledge Tracing: Simple and Efficient Student Modeling with Causal Relations", 2022, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Predicting anesthetic infusion events using machine learning", 2021, Scientific Reports
  • "Improving imbalanced classification using near-miss instances", 2022, Expert Systems with Applications

Frequent collaborators in research include:

  • Koh Takeuchi
  • Makoto Yamada
  • Guoxi Zhang
  • Ryoma Sato

Kashima has contributed to several book publications with Springer Science+Business Media and Springer Nature. Titles include "Advances in Knowledge Discovery and Data Mining" published in 2023 and "Advances in Artificial Intelligence" published in 2021.

Best Publications

  • Marginalized kernels between labeled graphs

    Hisashi Kashima;Koji Tsuda;Akihiro Inokuchi

  • Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation

    Masashi Sugiyama;Shinichi Nakajima;Hisashi Kashima;Paul V. Buenau

  • Direct importance estimation for covariate shift adaptation

    Masashi Sugiyama;Taiji Suzuki;Shinichi Nakajima;Hisashi Kashima

  • Eigenspace-based anomaly detection in computer systems

    Tsuyoshi Idé;Hisashi Kashima

  • Roughly balanced bagging for imbalanced data

    Shohei Hido;Hisashi Kashima;Yutaka Takahashi

  • Statistical outlier detection using direct density ratio estimation

    Shohei Hido;Yuta Tsuboi;Hisashi Kashima;Masashi Sugiyama

  • Estimation of low-rank tensors via convex optimization

    Ryota Tomioka;Kohei Hayashi;Hisashi Kashima

  • Tensor factorization using auxiliary information

    Atsuhiro Narita;Kohei Hayashi;Ryota Tomioka;Hisashi Kashima

  • A Parameterized Probabilistic Model of Network Evolution for Supervised Link Prediction

    Hisashi Kashima;Naoki Abe

  • Knowledge Tracing Machines: Factorization Machines for Knowledge Tracing

    Jill-Jenn Vie;Hisashi Kashima

  • Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction

    Hisashi Kashima;Tsuyoshi Kato;Yoshihiro Yamanishi;Masashi Sugiyama

  • Statistical Performance of Convex Tensor Decomposition

    Ryota Tomioka;Taiji Suzuki;Kohei Hayashi;Hisashi Kashima

  • Kernels for Semi-Structured Data

    Hisashi Kashima;Teruo Koyanagi

  • Direct Density Ratio Estimation for Large-scale Covariate Shift Adaptation

    Yuta Tsuboi;Hisashi Kashima;Shohei Hido;Steffen Bickel

  • Kernels for graphs

    H Kashima;K Tsuda;A Inokuchi;B. Schoelkopf K. Tsuda

  • A Linear-Time Graph Kernel

    Shohei Hido;Hisashi Kashima

  • Steered crowdsensing: incentive design towards quality-oriented place-centric crowdsensing

    Ryoma Kawajiri;Masamichi Shimosaka;Hisashi Kashima

  • Statistical quality estimation for general crowdsourcing tasks

    Yukino Baba;Hisashi Kashima

  • Training Conditional Random Fields Using Incomplete Annotations

    Yuta Tsuboi;Hisashi Kashima;Shinsuke Mori;Hiroki Oda

  • Roughly Balanced Bagging for Imbalanced Data.

    Shohei Hido;Hisashi Kashima

  • Approximation Ratios of Graph Neural Networks for Combinatorial Problems

    Ryoma Sato;Makoto Yamada;Hisashi Kashima

Frequent Co-Authors

Ryota Tomioka
Ryota Tomioka Microsoft (United States)
Koji Tsuda
Koji Tsuda University of Tokyo
Yoshihiro Yamanishi
Yoshihiro Yamanishi Nagoya University
Taiji Suzuki
Taiji Suzuki University of Tokyo
Xu Sun
Xu Sun Peking University
Toshihisa Takagi
Toshihisa Takagi University of Tokyo
Yuya Kajikawa
Yuya Kajikawa University of Tokyo
Toshiyuki Tanaka
Toshiyuki Tanaka Kyoto University

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