Daniel Jarrett

Stepwise Model Selection for Sequence Prediction via Deep Kernel Learning

2020 · arXiv (Cornell University)

An essential problem in automated machine learning (AutoML) is that of model selection. A unique challenge in the sequential setting is the fact that the optimal model itself may vary over time, depending on the …

Explaining by Imitating: Understanding Decisions by Interpretable Policy Learning

2023 · arXiv (Cornell University)

Understanding human behavior from observed data is critical for transparency and accountability in decision-making. Consider real-world settings such as healthcare, in which modeling a decision-maker's policy is challenging -- with no access to underlying states, …

Language Agents as Digital Representatives in Collective Decision-Making

2025 · arXiv (Cornell University)

Consider the process of collective decision-making, in which a group of individuals interactively select a preferred outcome from among a universe of alternatives. In this context, "representation" is the activity of making an individual's preferences …