| Computing Valid p-value for Optimal Changepoint by Selective Inference using Dynamic Programming VNL Duy, H Toda, R Sugiyama, I Takeuchi 34th Conference on Neural Information Processing Systems (NeurIPS 2020), 2020 | 38 | 2020 |
| Parametric Programming Approach for More Powerful and General Lasso Selective Inference VNL Duy, I Takeuchi International Conference on Artificial Intelligence and Statistics (AISTATS …, 2020 | 28* | 2020 |
| More Powerful Conditional Selective Inference for Generalized Lasso by Parametric Programming VN Le Duy, I Takeuchi Journal of Machine Learning Research 23 (300), 1-37, 2022 | 25 | 2022 |
| Quantifying Statistical Significance of Neural Network-based Image Segmentation by Selective Inference VN Le Duy, S Iwazaki, I Takeuchi Advances in Neural Information Processing Systems, 2022 | 24* | 2022 |
| More Powerful and General Selective Inference for Stepwise Feature Selection using Homotopy Method K Sugiyama, VN Le Duy, I Takeuchi International Conference on Machine Learning, 9891-9901, 2021 | 18 | 2021 |
| Conditional selective inference for robust regression and outlier detection using piecewise-linear homotopy continuation T Tsukurimichi, Y Inatsu, VNL Duy, I Takeuchi Annals of the Institute of Statistical Mathematics, 1-32, 2022 | 14 | 2022 |
| Fast and more powerful selective inference for sparse high-order interaction model D Das, VN Le Duy, H Hanada, K Tsuda, I Takeuchi Proceedings of the AAAI Conference on Artificial Intelligence 36 (9), 9999-10007, 2022 | 11 | 2022 |
| Valid and Exact Statistical Inference for Multi-dimensional Multiple Change-Points by Selective Inference R Sugiyama, H Toda, VNL Duy, Y Inatsu, I Takeuchi arXiv preprint arXiv:2110.08989, 2021 | 10 | 2021 |
| Exact statistical inference for the wasserstein distance by selective inference VNL Duy, I Takeuchi Annals of the Institute of Statistical Mathematics, 1-31, Springer Japan, 2022 | 7* | 2022 |
| Valid P-Value for Deep Learning-driven Salient Region M Daiki, VN Le Duy, I Takeuchi The Eleventh International Conference on Learning Representations, 2023 | 6* | 2023 |
| Statistical Inference for the Dynamic Time Warping Distance, with Application to Abnormal Time-Series Detection VNL Duy, I Takeuchi arXiv preprint arXiv:2202.06593, 2022 | 4* | 2022 |
| Stat-DSM: Statistically Discriminative Sub-Trajectory Mining With Multiple Testing Correction VN Le Duy, T Sakuma, T Ishiyama, H Toda, K Arai, M Karasuyama, ... IEEE Transactions on Knowledge and Data Engineering 34 (3), 1477-1488, 2020 | 3 | 2020 |
| Bounded P-values in Parametric Programming-based Selective Inference T Shiraishi, D Miwa, VNL Duy, I Takeuchi arXiv preprint arXiv:2307.11351, 2023 | 1 | 2023 |
| Multi-agent statistical discriminative sub-trajectory mining and an application to NBA basketball R Bunker, VN Le Duy, Y Tabei, I Takeuchi, K Fujii | 1 | 2023 |
| Statistically Discriminative Sub-trajectory Mining VNL Duy, T Sakuma, T Ishiyama, H Toda, K Nishi, M Karasuyama, ... arXiv preprint arXiv:1905.01788, 2019 | 1 | 2019 |
| Statistical Test for Generated Hypotheses by Diffusion Models T Katsuoka, T Shiraishi, D Miwa, VNL Duy, I Takeuchi arXiv preprint arXiv:2402.11789, 2024 | | 2024 |
| Statistical Test for Anomaly Detections by Variational Auto-Encoders D Miwa, T Shiraishi, VNL Duy, T Katsuoka, I Takeuchi arXiv preprint arXiv:2402.03724, 2024 | | 2024 |
| Statistical Test for Attention Map in Vision Transformer T Shiraishi, D Miwa, T Katsuoka, VNL Duy, K Taji, I Takeuchi arXiv preprint arXiv:2401.08169, 2024 | | 2024 |
| Selective Inference for Changepoint detection by Recurrent Neural Network T Shiraishi, D Miwa, VNL Duy, I Takeuchi arXiv preprint arXiv:2311.14964, 2023 | | 2023 |
| CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference VNL Duy, HT Lin, I Takeuchi arXiv preprint arXiv:2310.14608, 2023 | | 2023 |
Takeuchi IchiroProfessor, Nagoya UniversityVerified email at mae.nagoya-u.ac.jp
