Feb. 1, 2024, 12:42 p.m. | Yixin Cheng Grigorios G. Chrysos Markos Georgopoulos Volkan Cevher

cs.CV updates on arXiv.org arxiv.org

Despite the remarkable capabilities of deep neural networks in image recognition, the dependence on activation functions remains a largely unexplored area and has yet to be eliminated. On the other hand, Polynomial Networks is a class of models that does not require activation functions, but have yet to perform on par with modern architectures. In this work, we aim close this gap and propose MONet, which relies solely on multilinear operators. The core layer of MONet, called Mu-Layer, captures multiplicative …

architectures capabilities class cs.cv cs.lg functions image image recognition modern networks neural networks polynomial recognition work

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