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Differentiable Earth Mover's Distance for Data Compression at the High-Luminosity LHC
The Earth mover's distance (EMD) is a useful metric for image recognition and classification, but its usual implementations are not differentiable or too slow to be used as a loss function for training other algorithms via gradient descent. In this paper, we train a convolutional neural network...
Autores principales: | Shenoy, Rohan, Duarte, Javier, Herwig, Christian, Hirschauer, James, Noonan, Daniel, Pierini, Maurizio, Tran, Nhan, Mantilla Suarez, Cristina |
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Lenguaje: | eng |
Publicado: |
2023
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Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2861959 |
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