30 citations · 46 across the 4 of their papers we have counts for
4 papers
Data Efficiency for Large Recommendation Models
Kshitij Jain, Jingru Xie, Kevin Regan +9
Large recommendation models (LRMs) are fundamental to the multi-billion dollar online advertising industry, processing massive datasets of hundreds of billions of examples before t…
On the Factory Floor: ML Engineering for Industrial-Scale Ads Recommendation Models
Rohan Anil, Sandra Gadanho, Da Huang +9
For industrial-scale advertising systems, prediction of ad click-through rate (CTR) is a central problem. Ad clicks constitute a significant class of user engagements and are often…
Scalable Second Order Optimization for Deep Learning
Rohan Anil, Vineet Gupta, Tomer Koren +2
Optimization in machine learning, both theoretical and applied, is presently dominated by first-order gradient methods such as stochastic gradient descent. Second-order optimizatio…
Large Margin Deep Networks for Classification
Gamaleldin F. Elsayed, Dilip Krishnan, Hossein Mobahi +2
We present a formulation of deep learning that aims at producing a large margin classifier. The notion of margin, minimum distance to a decision boundary, has served as the foundat…