2 papers
cs.LG2024
Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning
Dake Zhang, Boxiang Lyu, Shuang Qiu +2
We study risk-sensitive reinforcement learning (RL), a crucial field due to its ability to enhance decision-making in scenarios where it is essential to manage uncertainty and mini…
cs.GT2023
Pairwise Ranking Losses of Click-Through Rates Prediction for Welfare Maximization in Ad Auctions
Boxiang Lyu, Zhe Feng, Zachary Robertson +1
We study the design of loss functions for click-through rates (CTR) to optimize (social) welfare in advertising auctions. Existing works either only focus on CTR predictions withou…