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update krum readme with parameter details.
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Yi-Zoey committed Aug 28, 2020
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**Krum proposed in: [Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent](https://papers.nips.cc/paper/6617-machine-learning-with-adversaries-byzantine-tolerant-gradient-descent.pdf)**

This example explains how to run the KRUM fusion algorithm on CNNs implemented with Keras training
This example explains how to run the Krum fusion algorithm to train CNNs implemented with Keras training
on [MNIST](http://yann.lecun.com/exdb/mnist/) data. Data in this example preprocessed by scaling down to range from `[0, 255]` to `[0, 1]`.
No other preprocessing is performed.

**Note that** the parameter `byzantine_threshold` is set to `1` by default. According to Krum's assumption, the number of parties in the FL system should be at least `2 * byzantine_threshold + 3`. Therefore, to run this example, please create at least `5` parties.

- Split data by running:

```
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