53 citations · 58 across the 6 of their papers we have counts for
3 papers · 1 filter
Accelerating Recommender Model Training by Dynamically Skipping Stale Embeddings
Yassaman Ebrahimzadeh Maboud, Muhammad Adnan, Divya Mahajan +1
Training recommendation models pose significant challenges regarding resource utilization and performance. Prior research has proposed an approach that categorizes embeddings into…
Ad-Rec: Advanced Feature Interactions to Address Covariate-Shifts in Recommendation Networks
Muhammad Adnan, Yassaman Ebrahimzadeh Maboud, Divya Mahajan +1
Recommendation models are vital in delivering personalized user experiences by leveraging the correlation between multiple input features. However, deep learning-based recommendati…
Accelerating Recommendation System Training by Leveraging Popular Choices
Muhammad Adnan, Yassaman Ebrahimzadeh Maboud, Divya Mahajan +1
Recommender models are commonly used to suggest relevant items to a user for e-commerce and online advertisement-based applications. These models use massive embedding tables to st…