8 citations · 22 across the 25 of their papers we have counts for
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stat.ML2026
Small Gradient Norm Regret for Online Convex Optimization
Wenzhi Gao, Chang He, Madeleine Udell
This paper introduces a new problem-dependent regret measure for online convex optimization with smooth losses. The notion, which we call the regret, depends on the cumul…
stat.ML2025
Beyond Regret: Decoupling Learning and Decision-making in Online Linear Programming
Wenzhi Gao, Dongdong Ge, Chenyu Xue +2
Online linear programming plays an important role in both revenue management and resource allocation, and recent research has focused on developing efficient first-order online lea…
stat.ML2024
Wait-Less Offline Tuning and Re-solving for Online Decision Making
Jingruo Sun, Wenzhi Gao, Ellen Vitercik +1
Online linear programming (OLP) has found broad applications in revenue management and resource allocation. State-of-the-art OLP algorithms achieve low regret by repeatedly solving…