7 accepted papers
We study a sequential resource allocation problem motivated by adaptive network recruitment, in which a limited budget of identical resources must be allocated over multiple rounds to individuals with stochastic referral capacity. Successful referrals endogenously generate future decision opportunit…
Poaching poses significant threats to biodiversity. A valuable step in reducing poaching is to forecast poacher behavior, which can inform patrol deployment and other conservation interventions. Existing poaching prediction methods based on linear models or decision trees lack the expressivity to ca
Existing alignment methods directly use the reward model learned from user preference data to optimize an LLM policy, subject to KL regularization with respect to the base policy. This practice is suboptimal for maximizing user's utility because the KL regularization may cause the LLM to inherit the…
Reducing preventable maternal mortality remains a global health priority. Under Sustainable Development Goal (SDG) target 3.1, the WHO emphasizes timely and equitable allocation of limited maternal health resources. Motivated by Department of Obstetrics and Gynecology at several important hospitals
Researchers strategically choose where to submit their work in order to maximize its impact, and these publication decisions in turn determine venues
Incorporating pre-collected offline data from a source environment can significantly improve the sample efficiency of reinforcement learning (RL), but this benefit is often challenged by discrepancies between the transition dynamics of the source and target environments. Existing methods typically a…
In green security, defenders must forecast adversarial behavior-such as poaching, illegal logging, and illegal fishing-to plan effective patrols. These behavior are often highly uncertain and complex. Prior work has leveraged game theory to design robust patrol strategies to handle uncertainty, but