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Recent work has revealed many intriguing empirical phenomena in neural network training, despite the poorly understood and highly complex loss landscapes and training dynamics.
Assignment problems and the location of economic activities
Tjalling C Koopmans and Martin Beckmann · 1957
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Uniform convergence may be unable to explain generalization in deep learning
Federated learning with matched averaging
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Deep neural network fusion via graph matching with applications to model ensemble and federated learning
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Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time
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