The data scientist's guide for writing papers
Abstract:
The goal of this tutorial is to provide guidelines and good practices on how to write scientific papers, with emphasis on writing technical sections. The tutorial consists of two parts. In the first part we will go over general philosophy for designing and typesetting mathematical notation, describing experiments, typesetting pseudo-code and tables, as well as, writing proofs. In addition, we will highlight typical mistakes done in computer science papers. The second part will focus on designing and typesetting high-quality visualizations. Here, our goal is two-fold: (i) we provide tools and ideas for designing complex non-standard visualizations, (ii) we provide guidelines on how to typeset standard plots, and highlight common errors done in data mining papers.
The tutorial will be given at ECML PKDD 2016.