Photorealistic Reconstruction from First Principles
Sara Fridovich-Keil [2023]

Incorporating Intent, Impact, and Context for Beneficial Machine Learning
Esther Rolf [2022]

Reliable Machine Learning in Feedback Systems
Sarah Dean [2021]

Statistical Complexity and Regret in Linear Control
Max Simchowitz [2021]

From Distribution Shift to Kernel Methods: A study of empirical phenomena in machine learning
Vaishaal Shankar [2020]

The sample complexity of simple reinforcement learning
Horia Mania [2020]

Evaluation of Methods for Data-Driven Tools that Empower Mental Health Professionals
Orianna DeMasi [2019]

Measuring Generalization and Overfitting in Machine Learning
Rebecca Roelofs [2019]

Performance Guarantees in Learning and Robust Control
Ross Boczar [2019]

Sample Complexity Bounds for the Linear Quadratic Regulator
Stephen Tu [2019]