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Large Neural Networks Learning from Scratch with Very Few Data and
  without Explicit Regularization
v1v2 (latest)

Large Neural Networks Learning from Scratch with Very Few Data and without Explicit Regularization

International Conference on Machine Learning and Computing (ICMLC), 2022
18 May 2022
C. Linse
T. Martinetz
    SSLVLM
ArXiv (abs)PDFHTML

Papers citing "Large Neural Networks Learning from Scratch with Very Few Data and without Explicit Regularization"

3 / 3 papers shown
Enhancing Generalization in Convolutional Neural Networks through
  Regularization with Edge and Line Features
Enhancing Generalization in Convolutional Neural Networks through Regularization with Edge and Line FeaturesInternational Conference on Artificial Neural Networks (ICANN), 2024
C. Linse
Beatrice Brückner
Thomas Martinetz
139
1
0
22 Oct 2024
Rethinking generalization of classifiers in separable classes scenarios
  and over-parameterized regimes
Rethinking generalization of classifiers in separable classes scenarios and over-parameterized regimesIEEE International Joint Conference on Neural Network (IJCNN), 2024
Julius Martinetz
C. Linse
Thomas Martinetz
329
0
0
22 Oct 2024
Do highly over-parameterized neural networks generalize since bad
  solutions are rare?
Do highly over-parameterized neural networks generalize since bad solutions are rare?IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
Julius Martinetz
T. Martinetz
427
1
0
07 Nov 2022
1