Implicit self-regularization in deep neural networks: Evidence from random matrix theory and implications for learning

被引：0
|
作者：
Martin, Charles H. [1 ]
Mahoney, Michael W. [2 ,3 ]
机构：
[1] Martin, Charles H.
[2] 2,Mahoney, Michael W.
来源：
| 1600年 / Microtome Publishing卷 / 22期
关键词：
Random variables;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
引用
收藏
相关论文
共 50 条
  • [31] Learning curves for overparametrized deep neural networks: A field theory perspective
    Cohen, Omry
    Malka, Or
    Ringel, Zohar
    PHYSICAL REVIEW RESEARCH, 2021, 3 (02):
  • [32] Deep Learning for Telecom Self-Optimized Networks: Benefits and Implications
    Alhaqui, Farah
    Lahsen-Cherif, Iyad
    Elkhechafi, Mariam
    Elkhadimi, Ahmed
    IEEE ACCESS, 2024, 12 : 195422 - 195435
  • [33] Neural learning rules from associative networks theory
    Lotito, Daniele
    NEUROCOMPUTING, 2025, 636
  • [34] Recovering from Random Pruning: On the Plasticity of Deep Convolutional Neural Networks
    Mittal, Deepak
    Bhardwaj, Shweta
    Khapra, Mitesh M.
    Ravindran, Balaraman
    2018 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV 2018), 2018, : 848 - 857
  • [35] A Deep Dive into Machine Learning: The Roles of Neural Networks and Random Forests in QSPR Analysis
    Ahmed, Wakeel
    Ashraf, Tamseela
    Almutairi, Dalal
    Zaman, Shahid
    Ahmed, Shakeel
    Ehsan, Huma
    BIONANOSCIENCE, 2025, 15 (01)
  • [36] Sentiment analysis based on rhetorical structure theory:Learning deep neural networks from discourse trees
    Kraus, Mathias
    Feuerriegel, Stefan
    EXPERT SYSTEMS WITH APPLICATIONS, 2019, 118 : 65 - 79
  • [37] From Pioneering Artificial Neural Networks to Deep Learning and Beyond
    Foresti, Gian Luca
    INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, 2021, 31 (05)
  • [38] Learning Without Feedback: Fixed Random Learning Signals Allow for Feedforward Training of Deep Neural Networks
    Frenkel, Charlotte
    Lefebvre, Martin
    Bol, David
    FRONTIERS IN NEUROSCIENCE, 2021, 15
  • [39] Learning From Noisy Labels With Deep Neural Networks: A Survey
    Song, Hwanjun
    Kim, Minseok
    Park, Dongmin
    Shin, Yooju
    Lee, Jae-Gil
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2023, 34 (11) : 8135 - 8153
  • [40] The Development of Neural Networks applications from Perceptron to Deep Learning
    Al-Mahasneh, Ahmad Jobran
    Anavatti, Sreenatha G.
    Garratt, Matthew A.
    2017 INTERNATIONAL CONFERENCE ON ADVANCED MECHATRONICS, INTELLIGENT MANUFACTURE, AND INDUSTRIAL AUTOMATION (ICAMIMIA), 2017, : 1 - 6
12345