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03/27/2023
Lifting uniform learners via distributional decomposition
We show how any PAC learning algorithm that works under the uniform dist...
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06/17/2022
Popular decision tree algorithms are provably noise tolerant
Using the framework of boosting, we prove that all impurity-based decisi...
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11/19/2021
On the power of adaptivity in statistical adversaries
We study a fundamental question concerning adversarial noise models in s...
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06/19/2019
Calibrated Model-Based Deep Reinforcement Learning
Estimates of predictive uncertainty are important for accurate model-bas...
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06/05/2019
The Stanford Acuity Test: A Probabilistic Approach for Precise Visual Acuity Testing
Chart-based visual acuity measurements are used by billions of people to...
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05/31/2019
Using Latent Variable Models to Observe Academic Pathways
Understanding large-scale patterns in student course enrollment is a pro...
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05/23/2019
Generative Grading: Neural Approximate Parsing for Automated Student Feedback
Open access to high-quality education is limited by the difficulty of pr...
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04/01/2019
