567 citations · 758 across the 8 of their papers we have counts for
4 papers · 1 filter
Nonlinear Initialization Methods for Low-Rank Neural Networks
Kiran Vodrahalli, Rakesh Shivanna, Maheswaran Sathiamoorthy +2
We propose a novel low-rank initialization framework for training low-rank deep neural networks -- networks where the weight parameters are re-parameterized by products of two low-…
Understanding and Improving Knowledge Distillation
Jiaxi Tang, Rakesh Shivanna, Zhe Zhao +4
Knowledge Distillation (KD) is a model-agnostic technique to improve model quality while having a fixed capacity budget. It is a commonly used technique for model compression, wher…
Towards Neural Mixture Recommender for Long Range Dependent User Sequences
Jiaxi Tang, Francois Belletti, Sagar Jain +4
Understanding temporal dynamics has proved to be highly valuable for accurate recommendation. Sequential recommenders have been successful in modeling the dynamics of users and ite…
Top-K Off-Policy Correction for a REINFORCE Recommender System
Minmin Chen, Alex Beutel, Paul Covington +3
Industrial recommender systems deal with extremely large action spaces -- many millions of items to recommend. Moreover, they need to serve billions of users, who are unique at any…