10 papers
Effective Personalized AI Tutors via LLM-Guided Reinforcement Learning
Angel Tsai-Hsuan Chung, Botong Zhang, Ling-Chieh Kung +2
Generative AI (GenAI) is rapidly reshaping education by unlocking the potential for personalized tutoring. Yet, emerging platforms largely focus on GenAI chatbot tutors that reacti…
Improving Access to Essential Medicines via Decision-Aware Machine Learning
Angel Tsai-Hsuan Chung, Jatu Abdulai, Patrick Bayoh +4
A critical challenge in healthcare systems in low- and middle-income countries (LMICs) is the efficient and equitable allocation of scarce resources, particularly essential medicin…
A Hierarchy of Policy Learning Problems
Hamsa Bastani, Osbert Bastani, Shihan Chen
Policy learning has received substantial attention with the goal of learning policies from observational data for decision-making. A majority of work in this space has focused on d…
Learning to target with network interference
Xiaomeng Wang, Hamsa Bastani, Osbert Bastani +1
This paper studies adaptive targeting under network interference in a bandit setting, where treatments applied to one individual may affect others through spillover effects. We con…
Winner's Curse Drives False Promises in Data-Driven Decisions
Hamsa Bastani, Osbert Bastani, Bryce McLaughlin
A major challenge in data-driven decision-making is accurate policy evaluation---i.e., guaranteeing that a learned decision-making policy achieves the promised benefits. A popular…
Are AI Capabilities Increasing Exponentially? A Competing Hypothesis
Haosen Ge, Hamsa Bastani, Osbert Bastani
Rapidly increasing AI capabilities have substantial real-world consequences, ranging from AI safety concerns to labor market consequences. The Model Evaluation & Threat Research (M…
Beating the Winner's Curse via Inference-Aware Policy Optimization
Hamsa Bastani, Osbert Bastani, Bryce McLaughlin
There has been a surge of recent interest in automatically learning policies to target treatment decisions based on rich individual covariates. In addition, practitioners want conf…
Strategic Hiring under Algorithmic Monoculture
Jackie Baek, Hamsa Bastani, Shihan Chen
We study the impact of strategic behavior in labor markets characterized by algorithmic monoculture, where firms compete for a shared pool of applicants using a common algorithmic…
Stochastic Bandits with ReLU Neural Networks
Kan Xu, Hamsa Bastani, Surbhi Goel +1
We study the stochastic bandit problem with ReLU neural network structure. We show that a regret guarantee is achievable by considering bandits with one-layer…
Stochastic Online Conformal Prediction with Semi-Bandit Feedback
Haosen Ge, Hamsa Bastani, Osbert Bastani
Conformal prediction has emerged as an effective strategy for uncertainty quantification by modifying a model to output sets of labels instead of a single label. These prediction s…