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cs.LG2024
On Expressive Power of Quantized Neural Networks under Fixed-Point Arithmetic
Yeachan Park, Sejun Park, Geonho Hwang
Existing works on the expressive power of neural networks typically assume real parameters and exact operations. In this work, we study the expressive power of quantized networks u…
cs.LG2024
Expressive Power of ReLU and Step Networks under Floating-Point Operations
Yeachan Park, Geonho Hwang, Wonyeol Lee +1
The study of the expressive power of neural networks has investigated the fundamental limits of neural networks. Most existing results assume real-valued inputs and parameters as w…