Vo Nguyen Le Duy

^[new] CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference Paper
V.N.L. Duy, H.-T. Lin, I. Takeuchi
International Conference on Artificial Intelligence and Statistics (AISTATS 2024). Acceptance rate 27.6%.
Valid P-Value for Deep Learning-Driven Salient Region Paper Code
D. Miwa, V.N.L. Duy (co-first), I. Takeuchi
International Conference on Learning Representations (ICLR 2023). Acceptance rate 31.8%.
More Powerful Conditional Selective Inference for Generalized Lasso by Parametric Programming Paper Code
V.N.L. Duy, I. Takeuchi
Journal of Machine Learning Research (JMLR), 2022. IF in 2018 = 4.091.
Quantifying Statistical Significance of Neural Network-based Image Segmentation by Selective Inference Paper Code
V.N.L. Duy, S. Iwazaki, I. Takeuchi
Neural Information Processing Systems (NeurIPS 2022). Acceptance rate 25.6%.
Computing Valid p-value for Optimal Changepoint by Selective Inference using Dynamic Programming
V.N.L. Duy, H. Toda (co-first), R. Sugiyama, I. Takeuchi
Neural Information Processing Systems (NeurIPS 2020). Accepted as Spotlight, top 4.0% = (105+280)/9454.
Paper Code Spotlight Talk Poster

Publications

Bounded P-values in Parametric Programming-based Selective Inference Paper Code
T. Shiraishi, D. Miwa, V.N.L. Duy, I. Takeuchi
Japanese Journal of Statistics and Data Science, 2024. IF in 2023 = 1.3.
Exact Statistical Inference for the Wasserstein Distance by Selective Inference Paper Code
V.N.L. Duy, I. Takeuchi
Annals of the Institute of Statistical Mathematics (AISM), 2022. IF in 2020 = 1.267.
Conditional Selective Inference for Robust Regression and Outlier Detection using Piecewise-Linear Homotopy Continuation Paper
T. Tsukurimichi, Y. Inatsu, V.N.L. Duy, I. Takeuchi
Annals of the Institute of Statistical Mathematics (AISM), 2022. IF in 2020 = 1.267.
Fast and More Powerful Selective Inference for Sparse High-order Interaction Model Paper
D. Das, V.N.L. Duy, H. Hanada, K. Tsuda, I. Takeuchi
AAAI Conference on Artificial Intelligence (AAAI 2022). Selected for Oral presentation. Acceptance rate 15%.
More Powerful and General Selective Inference for Stepwise Feature Selection using Homotopy Method Paper Code
K. Sugiyama, V.N.L. Duy (co-first), I. Takeuchi
International Conference on Machine Learning (ICML 2021). Acceptance rate 21.5%.
Parametric Programming Approach for More Powerful and General Lasso Selective Inference Paper Code
V.N.L. Duy, I. Takeuchi
International Conference on Artificial Intelligence and Statistics (AISTATS 2021). Acceptance rate 29.8%.
Stat-DSM: Statistically Discriminative Sub-trajectory Mining with Multiple Testing Correction Paper Code
V.N.L. Duy, T. Sakuma, T. Ishiyama, H. Toda, K. Arai, M. Karasuyama, Y. Okubo, M. Sunaga, H. Hanada, Y. Tabei, I. Takeuchi
IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE). IF in 2019 = 4.935.
Statistically Discriminative Sub-trajectory Mining with Multiple Testing Correction Paper Code
V.N.L. Duy, T. Sakuma, T. Ishiyama, H. Toda, K. Arai, M. Karasuyama, Y. Okubo, M. Sunaga, H. Hanada, Y. Tabei, I. Takeuchi
International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2019).

Preprints

Statistical Test for Generated Hypotheses by Diffusion Model Paper Code
T. Katsuoka, T. Shiraishi, D. Miwa, V.N.L. Duy, I. Takeuchi
ArXiv, 2024
Statistical Test for Anomaly Detections by Variational Auto-Encoders Paper Code
D. Miwa, T. Shiraishi, V.N.L. Duy, T. Katsuoka, I. Takeuchi
ArXiv, 2024
Statistical Test for Attention Map in Vision Transformer Paper Code
T. Shiraishi, D. Miwa, T. Katsuoka, V.N.L. Duy, K. Taji, I. Takeuchi
ArXiv, 2024
Selective Inference for Changepoint Detection by Recurrent Neural Network Paper Code
T. Shiraishi, D. Miwa, V.N.L. Duy, I. Takeuchi
ArXiv, 2023
Multi-agent Statistical Discriminative Sub-trajectory Mining and an Application to NBA Basketball Paper Code
R. Bunker, V.N.L. Duy, Y. Tabei, I. Takeuchi, K. Fujii
ArXiv, 2023
Statistical Inference for the Dynamic Time Warping Distance, with Application to Abnormal Time-Series Detection
V.N.L. Duy, I. Takeuchi
ArXiv, 2022 Paper Code
Valid and Exact Statistical Inference for Multi-dimensional Multiple Change-Points by Selective Inference Paper
R. Sugiyama, H. Toda, V.N.L. Duy, Y. Inatsu, I. Takeuchi
ArXiv, 2021

Talks

2023/5/24
International Seminar on Selective Inference, Online
Parametric Programming for More Powerful Conditional Selective Inference, with Applications to Deep Learning-Based Image Segmentation and Salient Region Detection
2023/4/20
Japan-Vietnam AI Forum, Hanoi, Vietnam
Exact Statistical Inference for the Wasserstein Distance
2023/3/13
Workshop on Optimization and Machine Learning, Nuremberg and Waischenfeld, Germany
Statistical Inference for Neural Network-based Image Segmentation
2023/3/10
EPFL-CIS and RIKEN-AIP Joint Workshop on Machine Learning and Artificial Intelligence, Lausanne, Switzerland
Statistical Inference for Neural Network-based Image Segmentation
EPFL-CIS & RIKEN-AIP Joint Online Workshop on Machine Learning 2022 [Video]
Exact Statistical Inference for the Wasserstein Distance by Selective Inference
RIKEN AIP Open Seminar 2020 [Video]
Statistically Quantifying the Reliability of Data-Driven Science by Selective Inference
Asian Conference on Machine Learning (ACML 2019) Workshop
Statistical Significance of Discriminative Sub-Trajectory

Biography

Education

Job Experience

Sep 2023 - present, Lecturer, University of Information Technology, Vietnam National University - HCMC, Vietnam.
Jan 2024 - present, Visiting Scientist, RIKEN, Japan.
Jan 2023 - Dec 2023, Postdoctoral Researcher, RIKEN, Japan.
Apr 2023 - Dec 2023, Visiting Researcher, Nagoya University, Japan.
June 2023, Exchange Faculty, Computational Learning Lab, National Taiwan University, Taiwan.
Apr 2020 - Dec 2022, Junior Research Associate, RIKEN, Japan.

Vo Nguyen Le Duy

Vo Nguyen Le Duy (Ph.D.)

Selected Papers

Publications

Preprints

Talks

Biography

Education

Job Experience