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stat.ML2026
How Does the ReLU Activation Affect the Implicit Bias of Gradient Descent on High-dimensional Neural Network Regression?
Kuo-Wei Lai, Guanghui Wang, Molei Tao +1
Overparameterized ML models, including neural networks, typically induce underdetermined training objectives with multiple global minima. The implicit bias refers to the limiting g…
stat.ML2025
Task Shift: From Classification to Regression in Overparameterized Linear Models
Tyler LaBonte, Kuo-Wei Lai, Vidya Muthukumar
Modern machine learning methods have recently demonstrated remarkable capability to generalize under task shift, where latent knowledge is transferred to a different, often more di…
stat.ML2024
Sharp analysis of out-of-distribution error for "importance-weighted" estimators in the overparameterized regime
Kuo-Wei Lai, Vidya Muthukumar
Overparameterized models that achieve zero training error are observed to generalize well on average, but degrade in performance when faced with data that is under-represented in t…