2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.IR2024
Async Learned User Embeddings for Ads Delivery Optimization
Mingwei Tang, Meng Liu, Hong Li +16
In recommendation systems, high-quality user embeddings can capture subtle preferences, enable precise similarity calculations, and adapt to changing preferences over time to maint…
cs.DB2023★ 2 cited
Moving Fast With Broken Data
Shreya Shankar, Labib Fawaz, Karl Gyllstrom +1
Machine learning (ML) models in production pipelines are frequently retrained on the latest partitions of large, continually-growing datasets. Due to engineering bugs, partitions i…