Author

Weihang Xu

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#machine learning Preprint Sep 2026

Learning Orthogonal Multi-Index Models Beyond Small Initialization: Incremental Learning, Competitive Dynamics and Symmetry

This work proves that incremental learning still occurs, and introduces a symmetry-based finite-width approximation via symmetrized networks, rather than comparing directly with an infinite-width limit, which yields better control of approximation errors and may be of independent interest.

Mo Zhou, Wei-Hang Xu, S. Du et al. · 0 citations

#machine learning Jun 2025

Global Convergence of Gradient EM for Over-Parameterized Gaussian Mixtures

This is the first global convergence and recovery result for EM or Gradient EM beyond the special case of m=2, and it is proved that with only mild over-parameterization, randomly initialized gradient EM converges to the ground truth with polynomial time and samples.

Mo Zhou, Weihang Xu, Maryam Fazel et al. · arXiv.org · 2 citations · ⚡1