219 citations · 461 across the 7 of their papers we have counts for
8 papers
Hawkeye: Reproducing GPU-Level Non-Determinism
Erez Badash, Dan Boneh, Ilan Komargodski +1
We present Hawkeye, a system for analyzing and reproducing GPU-level arithmetic operations. Using our framework, anyone can re-execute on a CPU the exact matrix multiplication oper…
Machine learning for modular multiplication
Kristin Lauter, Cathy Yuanchen Li, Krystal Maughan +2
Motivated by cryptographic applications, we investigate two machine learning approaches to modular multiplication: namely circular regression and a sequence-to-sequence transformer…
Do Users Write More Insecure Code with AI Assistants?
Neil Perry, Megha Srivastava, Deepak Kumar +1
We conduct the first large-scale user study examining how users interact with an AI Code assistant to solve a variety of security related tasks across different programming languag…
Question Generation for Adaptive Education
Megha Srivastava, Noah Goodman
Intelligent and adaptive online education systems aim to make high-quality education available for a diverse range of students. However, existing systems usually depend on a pool o…
Robustness to Spurious Correlations via Human Annotations
Megha Srivastava, Tatsunori Hashimoto, Percy Liang
The reliability of machine learning systems critically assumes that the associations between features and labels remain similar between training and test distributions. However, un…
An Empirical Analysis of Backward Compatibility in Machine Learning Systems
Megha Srivastava, Besmira Nushi, Ece Kamar +2
In many applications of machine learning (ML), updates are performed with the goal of enhancing model performance. However, current practices for updating models rely solely on iso…
The Effect of Learning Strategy versus Inherent Architecture Properties on the Ability of Convolutional Neural Networks to Develop Transformation Invariance
Megha Srivastava, Kalanit Grill-Spector
As object recognition becomes an increasingly common ML task, and recent research demonstrating CNNs vulnerability to attacks and small image perturbations necessitate fully unders…
Fairness Without Demographics in Repeated Loss Minimization
Tatsunori B. Hashimoto, Megha Srivastava, Hongseok Namkoong +1
Machine learning models (e.g., speech recognizers) are usually trained to minimize average loss, which results in representation disparity---minority groups (e.g., non-native speak…