1 citations · 1 across the 4 of their papers we have counts for
4 papers
Orbit: A Framework for Designing and Evaluating Multi-objective Rankers
Chenyang Yang, Tesi Xiao, Michael Shavlovsky +2
Machine learning in production needs to balance multiple objectives: This is particularly evident in ranking or recommendation models, where conflicting objectives such as user eng…
A Sinkhorn-type Algorithm for Constrained Optimal Transport
Xun Tang, Holakou Rahmanian, Michael Shavlovsky +3
Entropic optimal transport (OT) and the Sinkhorn algorithm have made it practical for machine learning practitioners to perform the fundamental task of calculating transport distan…
Accelerating Sinkhorn Algorithm with Sparse Newton Iterations
Xun Tang, Michael Shavlovsky, Holakou Rahmanian +4
Computing the optimal transport distance between statistical distributions is a fundamental task in machine learning. One remarkable recent advancement is entropic regularization a…
Field-wise Embedding Size Search via Structural Hard Auxiliary Mask Pruning for Click-Through Rate Prediction
Tesi Xiao, Xia Xiao, Ming Chen +1
Feature embeddings are one of the most essential steps when training deep learning based Click-Through Rate prediction models, which map high-dimensional sparse features to dense e…