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cs.LG2026
Two-Layer Linear Auto-Regressive Models Estimate Latent States
Yahya Sattar, Sunmook Choi, Leo Maynard-Zhang +3
Auto-regressive models have emerged as powerful tools for sequential data, from language to video. Understanding how and why these models learn latent representations remains an op…
cs.LG2026
Local linear convergence of gradient methods for overparameterized Gaussian mixtures
Jingxing Wang, Vasileios Charisopoulos, Maryam Fazel
We study the problem of learning Gaussian mixture models under overparameterization. Prior work has shown that while overparameterization is essential for avoiding spurious local o…