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WeightedEntropybased Quantization for Deep Neural Networks Unhook Park, Jungian AHN, and Sung Yew canusglow gmail.com, Jungian SNU.ac.KR, sung. Yew Gmail.com Seoul National University Computing and

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What is weighted entropy based quantization?

Weighted entropy based quantization is a method used in data compression to reduce the amount of data required to represent a signal.

Who is required to file weighted entropy based quantization?

Weighted entropy based quantization is typically used by data analysts and researchers in the field of signal processing.

How to fill out weighted entropy based quantization?

To fill out weighted entropy based quantization, one must calculate the weighted entropy of a signal and then use that information to quantize the data effectively.

What is the purpose of weighted entropy based quantization?

The purpose of weighted entropy based quantization is to efficiently compress data while minimizing loss of information.

What information must be reported on weighted entropy based quantization?

On weighted entropy based quantization, one must report the signal data, the calculated weighted entropy, and the quantization levels used.

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