Scale-invariant learning and convolutional networks

DOI10.1016/J.ACHA.2016.06.005zbMath1392.68340OpenAlexW786888796MaRDI QIDQ347531

Marc'Aurelio Ranzato, Wojciech Zaremba, Yuandong Tian, Mark Tygert, Soumith Chintala, Arthur D. Szlam

Publication date: 30 November 2016

Published in: Applied and Computational Harmonic Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.acha.2016.06.005

zbMATH Keywords

waveletsclassificationimage processingspectrumrepresentationinvariantsignal processingequivariantmachine learningwavelet packets

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Numerical methods for wavelets (65T60) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (1)

A Mathematical Motivation for Complex-Valued Convolutional Networks

Uses Software

• ElemStatLearn
• CIFAR

Cites Work

• Multicategory vertex discriminant analysis for high-dimensional data
• Nonlinear vertex discriminant analysis with reproducing kernels
• A Mathematical Motivation for Complex-Valued Convolutional Networks
• Unnamed Item

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