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Tao Luo

4 papers hereh-index 16 citations6 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1
  • last author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.LG3
  • math.DS1
same name
  • Tao Luo — 8 papers, h 2
  • Tao Luo — 6 papers, h 3
  • Tao Luo — 5 papers, h 3
  • Tao Luo — 4 papers, h 15
  • Tao Luo — 4 papers, h 3
  • Tao Luo — 3 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedArchitecture Induces Structural Invariant Manifolds of Neural Network Training Dynamics

1 citations · 1 across the 1 of their papers we have counts for

collaborators

4 papers

math.DS2026★ 1 cited

Architecture Induces Structural Invariant Manifolds of Neural Network Training Dynamics

Jiajie Zhao, Tao Luo, Yaoyu Zhang

While architecture is recognized as key to the performance of deep neural networks, its precise effect on training dynamics has been unclear due to the confounding influence of dat…

cs.LG2025

Embedding principle of homogeneous neural network for classification problem

Jiahan Zhang, Yaoyu Zhang, Tao Luo

In this paper, we study the Karush-Kuhn-Tucker (KKT) points of the associated maximum-margin problem in homogeneous neural networks, including fully-connected and convolutional neu…

cs.LG2025

Uncovering Critical Sets of Deep Neural Networks via Sample-Independent Critical Lifting

Leyang Zhang, Yaoyu Zhang, Tao Luo

This paper investigates the sample dependence of critical points for neural networks. We introduce a sample-independent critical lifting operator that associates a parameter of one…

cs.LG2025

Geometry and Local Recovery of Global Minima of Two-layer Neural Networks at Overparameterization

Leyang Zhang, Yaoyu Zhang, Tao Luo

Under mild assumptions, we investigate the geometry of the loss landscape for two-layer neural networks in the vicinity of global minima. Utilizing novel techniques, we demonstrate…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.