readme

README.md

@@ -65,7 +65,7 @@ Datasets used for the comparison benchmark of autoxgboost, Auto-WEKA and auto-sk
 
 Benchmark results are median percent error across 100 000 bootstrap samples (out of 25 runs) simulating 4 parallel runs. Bold numbers indicate best performing algorithms.
 
-# autoxgboost - How to Cite and Citing Publications
+# autoxgboost - How to Cite
 
 The **Automatic Gradient Boosting** framework was presented at the [ICML/IJCAI-ECAI 2018 AutoML Workshop](https://sites.google.com/site/automl2018icml/accepted-papers) ([poster](poster_2018.pdf)).  
 Please cite our [ICML AutoML workshop paper on arxiv](https://arxiv.org/abs/1807.03873v2).