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  • On the Existence of Global Minima and Convergence Analyses for Gradient Descent Methods in the Training of Deep Neural Networks

    Arnulf Jentzen, Adrian Riekert
    2022-07-06
    41548 4262 Pages:141-246 Open-access
  • Spectral Neural Networks: Approximation Theory and Optimization Landscape

    Chenghui Li, Rishi Sonthalia, Nicolás García Trillos
    2026-01-06
    123 206
  • Beyond the Quadratic Approximation: The Multiscale Structure of Neural Network Loss Landscapes

    Chao Ma, Daniel Kunin, Lei Wu, Lexing Ying
    2022-09-22
    39410 4502 Pages:247-267 Open-access
  • A Note on Continuous-Time Online Learning

    Lexing Ying
    2025-03-12
    11128 1041 Pages:1-10 Open-access
  • A Local Convergence Theory for the Stochastic Gradient Descent Method in Non-Convex Optimization with Non-Isolated Local Minima

    Taehee Ko, Xiantao Li
    2023-06-06
    26266 2620 Pages:138-160 Open-access
  • Soft-Constrained Distance Preserving t-SNE

    Joseph Balderas, Li Wang, Andrzej Korzeniowski, Ren-Cang Li
    2025-12-10
    247 80
  • Convergence of Stochastic Gradient Descent under a Local Łojasiewicz Condition for Deep Neural Networks

    Jing An, Jianfeng Lu
    2025-06-03
    8565 936 Pages:89-107 Open-access
  • Learning a Sparse Representation of Barron Functions with the Inverse Scale Space Flow

    Tjeerd Jan Heeringa, Tim Roith, Christoph Brune, Martin Burger
    2025-03-12
    11108 1232 Pages:48-88 Open-access
  • Approximation Results for Gradient Flow Trained Neural Networks

    Gerrit Welper
    2024-06-27
    25201 2568 Pages:107-175 Open-access
  • Semi-Supervised Clustering of Sparse Graphs: Crossing the Information-Theoretic Threshold

    Junda Sheng, Thomas Strohmer
    2024-03-21
    25185 2951 Pages:64-106 Open-access
  • RNN-Attention Based Deep Learning for Solving Inverse Boundary Problems in Nonlinear Marshak Waves

    Di Zhao, Weiming Li, Wengu Chen, Peng Song, Han Wang
    2023-06-06
    32949 4209 Pages:83-107 Open-access
  • The Cost-Accuracy Trade-Off in Operator Learning with Neural Networks

    Maarten V. de Hoop, Daniel Zhengyu Huang, Elizabeth Qian, Andrew M. Stuart
    2022-09-22
    40641 4304 Pages:299-341 Open-access
  • Embedding Principle: A Hierarchical Structure of Loss Landscape of Deep Neural Networks

    Yaoyu Zhang, Yuqing Li, Zhongwang Zhang, Tao Luo, Zhi-Qin John Xu
    2024-03-21
    80496 4499 Pages:60-113 Open-access
1 - 13 of 13 items
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