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stat.ME2025
Optimal Empirical Risk Minimization under Temporal Distribution Shifts
Yujin Jeong, Ramesh Johari, Dominik Rothenhäusler +1
Temporal distribution shifts pose a key challenge for machine learning models trained and deployed in dynamically evolving environments. This paper introduces RIDER (RIsk minimizat…
cs.AI2025
The Effect of State Representation on LLM Agent Behavior in Dynamic Routing Games
Lyle Goodyear, Rachel Guo, Ramesh Johari
Large Language Models (LLMs) have shown promise as decision-makers in dynamic settings, but their stateless nature necessitates creating a natural language representation of histor…