• 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)
  

• 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

Three papers were accepted for International Conference on Machine Learning (ICML 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.

Two papers accepted to NeurIPS 2020

• Ryoma Sato, Makoto Yamada, Hisashi Kashima.
  Fast Unbalanced Optimal Transport on a 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).

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 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.

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).