The following paper has been accepted to CVPR 2020!

• Yanbin Liu, Linchao Zhu, Makoto Yamada, Yi Yang.
  Semantic Correspondence as an Optimal Transport Problem
  IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020

The following paper has been accepted to ECAI 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.

Two papers accepted to AISTATS 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)

The following paper about crowdsourcing-based synthetic accessibility assessment of chemical compounds will appear in Expert Systems with Applications

Shun Ito, Yukino Baba, Tetsu Isomura, Hisashi Kashima.
Synthetic Accessibility Assessment Using Auxiliary Responses.
Expert Systems with Applications (ESWA), 2020.

The following paper has been accepted to AAAI 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.

Our paper titled “Dual Graph Convolutional Neural Network for Predicting Chemical Networks” will appear in BMC Bioinformatics.

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)

Two papers were accepted at ACML 2019.

• • Shogo Hayashi, Yoshinobu Kawahara, Hisashi Kashima.
    Active Change-Point Detection.
    In Proceedings of Asian Conference on Machine Learning (ACML), 2019.
  • Ryoma Sato, Makoto Yamada, Hisashi Kashima.
    Learning to Sample Hard Instances for Graph Algorithms.
    In Proceedings of Asian Conference on Machine Learning (ACML), 2019.

Five papers accepted at NeurIPS 2019.

• 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, Yasuhito 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).

Our paper was accepted for CIKM

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.

Two papers were accepted for The 24th International Conference on Neural Information Processing (ICONIP), Guangzhou, China.

Hirotaka Akita, Yukino Baba, Hisashi Kashima and 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 and Hisashi Kashima.
Quality Control for Crowdsourced Multi-Label Classification using RAkEL.
In Proceeding of the 24th International Conference on Neural Information Processing (ICONIP), 2017.

Three papers were accepted for ECML PKDD.

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.

A paper on quality control methods for crowdsourced hierarchical classification tasks has been accepted for 2015 IEEE International Conference on Data Mining (ICDM):
Naoki Otani, Yukino Baba, Hisashi Kashima.
Quality Control for Crowdsourced Hierarchical Classification.
In Proceedings of the 2015 IEEE International Conference on Data Mining (ICDM), Atlantic City, NJ, USA, 2015.

A paper on crowdsourcing for open data has been accepted for 2015 IEEE International Conference on Data Science and Advanced Analytics (DSAA):
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 IEEE International Conference on Data Science and Advanced Analytics (DSAA), 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), Hong Kong, China, 2015.

Two papers accepted for ACM SIGKDD 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), 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) , Sydney, Australia, 2015.

The tutorial slides for our PAKDD 2015 tutorial “Crowdsourcing for Big Data Analytics” are found here.