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Diversity Networks: Neural Network Compression Using Determinantal Point Processes
[article]
2017
arXiv
pre-print
We introduce Divnet, a flexible technique for learning networks with diverse neurons. Divnet models neuronal diversity by placing a Determinantal Point Process (DPP) over neurons in a given layer. It uses this DPP to select a subset of diverse neurons and subsequently fuses the redundant neurons into the selected ones. Compared with previous approaches, Divnet offers a more principled, flexible technique for capturing neuronal diversity and thus implicitly enforcing regularization. This enables
arXiv:1511.05077v6
fatcat:l4laul3l7vfdleqthpqq3fmh64