3 papers
stat.ML2025
Spectral Thresholds for Identifiability and Stability:Finite-Sample Phase Transitions in High-Dimensional Learning
William Hao-Cheng Huang
In high-dimensional learning, models remain stable until they collapse abruptly once the sample size falls below a critical level. This instability is not algorithm-specific but a…
stat.ML2025
Spectral Identifiability for Interpretable Probe Geometry
William Hao-Cheng Huang
Linear probes are widely used to interpret and evaluate neural representations, yet their reliability remains unclear, as probes may appear accurate in some regimes but collapse un…
cs.LG2024
Constrained Diffusion with Trust Sampling
William Huang, Yifeng Jiang, Tom Van Wouwe +1
Diffusion models have demonstrated significant promise in various generative tasks; however, they often struggle to satisfy challenging constraints. Our approach addresses this lim…