2 papers
cs.LG2025
Optimization of Epsilon-Greedy Exploration
Ethan Che, Hakan Ceylan, James McInerney +1
Modern recommendation systems rely on exploration to learn user preferences for new items, typically implementing uniform exploration policies (e.g., epsilon-greedy) due to their s…
cs.LG2024
Optimization-Driven Adaptive Experimentation
Ethan Che, Daniel R. Jiang, Hongseok Namkoong +1
Real-world experiments involve batched & delayed feedback, non-stationarity, multiple objectives & constraints, and (often some) personalization. Tailoring adaptive methods to addr…