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math.ST2026
Generalization error of min-norm interpolators in transfer learning
Yanke Song, Kenneth Gu, Sohom Bhattacharya +1
This paper establishes the generalization error of pooled min--norm interpolation in transfer learning, where data from diverse distributions are available. Min-norm interp…
math.ST2026
Self-Distillation is Optimal Among Spectral Shrinkage Estimators in Spiked Covariance Models
Radu Lecoiu, Debarghya Mukherjee, Pragya Sur
Self-distillation has emerged as a promising technique for improving model performance in modern machine learning systems. We develop the statistical foundations of self-distillati…
math.ST2025
Multi-Environment GLAMP: Approximate Message Passing for Transfer Learning with Applications to Lasso-based Estimators
Longlin Wang, Yanke Song, Kuanhao Jiang +1
Approximate Message Passing (AMP) algorithms enable precise characterization of certain classes of random objects in the high-dimensional limit, and have found widespread applicati…