12 citations · 15 across the 3 of their papers we have counts for
3 papers
Memory Layer: Train the In-Model Cache for Recommendation Models
Liangyuan Na, Gufan Yin, Yixin Bao +19
Early ranking stages in recommendation systems precompute item embeddings and cache them in-model for scoring within strict latency constraints. Because this cache exists only at s…
Patient Outcome Predictions Improve Operations at a Large Hospital Network
Liangyuan Na, Kimberly Villalobos Carballo, Jean Pauphilet +8
Problem definition: Access to accurate predictions of patients' outcomes can enhance medical staff's decision-making, which ultimately benefits all stakeholders in the hospitals. A…
The Benefit of Uncertainty Coupling in Robust and Adaptive Robust Optimization
Dimitris Bertsimas, Liangyuan Na, Bartolomeo Stellato +1
Despite the modeling power for problems under uncertainty, robust optimization (RO) and adaptive robust optimization (ARO) can exhibit too conservative solutions in terms of object…