- 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
Vo Nguyen Le Duy (Ph.D.) [ GitHub | Google Scholar | LinkedIn ]
Lecturer (a.k.a. Assistant Professor)University of Information Technology, Vietnam National University - HCM
Visiting Scientist
RIKEN Center for Advanced Intelligence Project
University Ambassador / Certified Instructor (AI for Anomaly Detection)
NVIDIA Deep Learning Institute
Email: vo.nl.duy[at]gmail.com or duyvnl[at]uit.edu.vn
Research interests: statistical machine learning, hypothesis testing, data mining.
I'm looking for motivated students interested in conducting ML research or pursuing a master's degree. If you're interested, please reach out via email (with CV and transcript).