KDD Deep Learning Day 2021 will take place on August 18, 8am-5pm PST.

7:50am 8:00am Opening Remarks Sameer Singh
8:00am 8:30am Invited Talk Eric Xing (MBZUAI/Petuum/CMU): "It is time for deep learning to understand its expense bills"
8:30am 8:45am Contributed Talk Arun Kumar (UC San Diego): "Some Damaging Delusions of Deep Learning Practice (and How to Avoid Them)
8:45am 9:15am Invited Talk Dawn Song (UC Berkeley): "Building towards a Responsible Data Economy"
9:15am 9:30am Invited Talk Deepak Agarwal (Pinterest): "Deep learning to power user engagement on Pinterest"
9:30am 9:45am Break
9:45am 10:15am Invited Talk Besmira Nushi (Microsoft Research): "On Debugging Machine Learning Models and Systems: Challenges, Myths, Tools"
10:15am 10:30am Contributed Talk Daniel Kang (Stanford): "Monitoring and Quality Assurance of Complex ML Deployments via Assertions"
10:30am 10:45am Contributed Talk Saket Gurukar (Ohio State University): "Unsupervised Network Representation Learning and the Illusion of Progress"
10:45am 11:15am Invited Talk Aleksander Madry (MIT): "Why Do ML Models Fail?"
11:15am 12:00pm Panel "Scaling and Debugging Deep Learning Systems" Panelists: Eric Xing, Deepak Agarwal, Besmira Nushi, Aleksander Madry, Arun Kumar, Daniel Kang, Saket Gurukar Moderators: Baharan Mirzasoleiman & Hima Lakkaraju
12:00pm 1:00pm Lunch
1:00pm 1:30pm Invited Talk James Zou (Stanford): "A data-centric view of trustworthy AI"
1:30pm 1:45pm Contributed Talk Harman Kaur (UMichigan): "Interpreting Interpretability: Understanding Data Scientists’ Use of Interpretability Tools for Machine Learning"
1:45pm 2:00pm Contributed Talk David Madras (UToronto): "Why Learn Fair Representations?"
2:00pm 2:30pm Invited Talk Martin Wattenberg (Google PAIR/Harvard CS): "Visualization for Human and Machine Learning"
2:30pm 2:45pm Break
2:45pm 3:15pm Invited Talk Jason Lee (Princeton): "Provable Representation Learning"
3:15pm 3:30pm Contributed Talk Andrew Stolman (KatanaGraph): "Studying the (in)-effectiveness of graph embeddings"
3:30pm 3:45pm Contributed Talk Tianlong Chen (UT Austin): "The lottery ticket hypothesis for gigantic pre-trained models"
3:45pm 4:15pm Invited Talk Yasaman Bahri (Google Brain): "Understanding Neural Scaling Laws"
4:15pm 5:00pm Panel "Understanding of DL Systems: Transparency, Fairness, and Theory" Panelists: James Zou, Yasaman Bahri, Martin Wattenberg, Harman Kaur, David Madras Moderators: Hima Lakkaraju & Baharan Mirzasoleiman
5:00pm Closing Remarks Xiang Ren