KDD 2020 Conference Highlights

The 2020 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining is a core conference in the AI/ML/DS field. The conference delivered on its promise of being all-encompassing in terms of breadth and depth of topics covered. Here are some highlights that can help you sharpen that saw of yours.

This post is in collaboration with Seong Kang, and Ian Horton.

The sessions highlighted are in no way a complete view of the KDD 2020 conference. The following sessions are covered in this post:

Sampled Topics

Best Research Paper Award

• Research Track: “On Sampled Metrics for Item Recommendation”

Recommendation systems

• Hands On Tutorial: Building Recommender Systems with PyTorch
• Hands On Tutorial: Deep Learning for Search and Recommender Systems in Practice

Bias, Ethical, and Responsible AI

• Hands On Tutorial: Dealing with Bias and Fairness in Data Science Systems: A Practical Hands-on Tutorial
• Toward Responsible AI by Planning to Fail
• Lessons from Archives: Strategies for Collecting Socio-cultural Data in Machine Learning