From f10d1a34515cff5a0c1bb85160aa6b10c892bab5 Mon Sep 17 00:00:00 2001
From: sjtudyq <48618508+sjtudyq@users.noreply.github.com>
Date: Fri, 25 Aug 2023 09:49:40 +0800
Subject: [PATCH] Update README.md

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 README.md | 2 ++
 1 file changed, 2 insertions(+)

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@@ -6,6 +6,8 @@ This code runs a benchmark for federated learning algorithms under non-IID data
 
 
 ## Updates on NIID-Bench
+We build a [leaderboard](https://niidbench.xtra.science) to enable researchers to test their own FL algorithms in our non-IID data partitioning framework. Welcome to submit your code and results in our [website](https://niidbench.xtra.science)!
+
 Implement `partition.py` to divide tabular datasets (csv format) into multiple files using our non-IID partitioning strategies. Column `Class` in the header is recognized as label. See an running example in `partition_to_file.sh`. The example dataset is [Credit Card Fraud Detection](https://www.kaggle.com/datasets/mlg-ulb/creditcardfraud).
 
 To adapt to your own tabular dataset in ​``partition.py``, you need the following steps: