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cs.LG2022
On Bridging the Gap between Mean Field and Finite Width in Deep Random Neural Networks with Batch Normalization
Amir Joudaki, Hadi Daneshmand, Francis Bach
Mean field theory is widely used in the theoretical studies of neural networks. In this paper, we analyze the role of depth in the concentration of mean-field predictions, specific…
cs.LG2022
Polynomial-time Sparse Measure Recovery: From Mean Field Theory to Algorithm Design
Hadi Daneshmand, Francis Bach
Mean field theory has provided theoretical insights into various algorithms by letting the problem size tend to infinity. We argue that the applications of mean-field theory go bey…