Virtual Special Session 11:
Machine Learning in Recommendation Systems
Many social media companies such as Facebook, Snap, Pinterest, Twitter etc generate bulk of their revenue from showing advertisements to users. The session aims to provide a working knowledge of how these social media companies leverage the power of Machine Learning and Optimization using big data to show relevant advertisements to users that come to their platform.
Chair: Dr. Praveen Kolli
Bio: Praveen Kolli is a Staff Machine Learning Engineer in the Ads Quality Team at DoorDash. Prior to that, he was a Senior Machine Learning Engineer working in the Ads Ranking Team at Pinterest. He builds deep learning models for showing relevant ads to the users. Before that, he worked at a startup called Houzz, where he built bidding algorithms for products that Houzz advertises on exchanges such as Google and Microsoft. Before that, he obtained his PhD in Mathematics from Carnegie Mellon University, Masters in Mathematics of Finance from Columbia University and Bachelors in Electrical Engineering from Indian Institute of Technology, Kharagpur.
Technical Committee
- Aayush Mudgal Senior Machine Learning Engineer at Pinterest, MS Columbia University; LinkedIn
- Jayash Koshal Staff Machine Learning Engineer at Meta, PhD University of Illinois Urbana-Champaign; LinkedIn
- Praneeth Boda Engineering Manager at LinkedIn, PhD University of Maryland; LinkedIn
- Bharath Bhat Senior Machine Learning Engineer at Google, MS Stanford University; LinkedIn
Paper Submission Instructions
All papers will be double-blind reviewed and must present original work.
- CMT Submission Site
- Select the track: Virtual Special Session 11: ML and Optimization in Ads Recommendation Systems
Papers submitted for reviewing should conform to IEEE specifications. Manuscript templates can be downloaded from:
Keydates
- Submission due date: September 5, 2023
- Notification of Acceptance: September 25, 2023
- Camera Ready Papers: October 5, 2023
- Pre-registration: October 15, 2023
- Conference: December 15-17, 2023
Registration
In order for your paper to be presented in the virtual session and published in the proceedings you must register to the conference.
Paper Presentation Instructions
The papers submitted to this track will be presented in the virtual part of the conference. There is no in-person presentation for this session.
If you decide to participate in-person to the conference you must have an adequate internet connection for your presentation and to participate in this special session.
ICMLA'23