Kuo-Wei Lai

11 papers A 1B 1Journal 8Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
How Does the ReLU Activation Affect the Implicit Bias of Gradient Descent on High-dimensional Neural Network Regression?
CoRR
Kuo-Wei Lai, Guanghui Wang, Molei Tao, Vidya Muthukumar
2025 J jnl
General Loss Functions Lead to (Approximate) Interpolation in High Dimensions.
J. Mach. Learn. Res.
Kuo-Wei Lai, Vidya Muthukumar
2025 A conf
Task Shift: From Classification to Regression in Overparameterized Linear Models.
AISTATS
Tyler LaBonte, Kuo-Wei Lai, Vidya Muthukumar
2025 J jnl
Task Shift: From Classification to Regression in Overparameterized Linear Models.
CoRR
Tyler LaBonte, Kuo-Wei Lai, Vidya Muthukumar
2024 B conf
Sharp Analysis of Out-of-Distribution Error for "Importance-Weighted" Estimators in the Overparameterized Regime.
ISIT
Kuo-Wei Lai, Vidya Muthukumar
2024 J jnl
Sharp analysis of out-of-distribution error for "importance-weighted" estimators in the overparameterized regime.
CoRR
Kuo-Wei Lai, Vidya Muthukumar
2023 J jnl
DeepSTI: Towards tensor reconstruction using fewer orientations in susceptibility tensor imaging.
Medical Image Anal.
Zhenghan Fang, Kuo-Wei Lai, Peter C. M. van Zijl, Xu Li, Jeremias Sulam
2023 J jnl
General Loss Functions Lead to (Approximate) Interpolation in High Dimensions.
CoRR
Kuo-Wei Lai, Vidya Muthukumar
2022 J jnl
DeepSTI: Towards Tensor Reconstruction using Fewer Orientations in Susceptibility Tensor Imaging.
CoRR
Zhenghan Fang, Kuo-Wei Lai, Peter C. M. van Zijl, Xu Li, Jeremias Sulam
2020 — conf
Learned Proximal Networks for Quantitative Susceptibility Mapping.
MICCAI (2)
Kuo-Wei Lai, Manisha Aggarwal, Peter C. M. van Zijl, Xu Li, Jeremias Sulam
2020 J jnl
Learned Proximal Networks for Quantitative Susceptibility Mapping.
CoRR
Kuo-Wei Lai, Manisha Aggarwal, Peter C. M. van Zijl, Xu Li, Jeremias Sulam