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]