3 papers
stat.ML2025
Optimizing ML Training with Metagradient Descent
Logan Engstrom, Andrew Ilyas, Benjamin Chen +3
A major challenge in training large-scale machine learning models is configuring the training process to maximize model performance, i.e., finding the best training setup from a va…
cs.SE2024
Input-Gen: Guided Generation of Stateful Inputs for Testing, Tuning, and Training
Ivan R. Ivanov, Joachim Meyer, Aiden Grossman +2
The size and complexity of software applications is increasing at an accelerating pace. Source code repositories (along with their dependencies) require vast amounts of labor to ke…
cs.PL2023
ComPile: A Large IR Dataset from Production Sources
Aiden Grossman, Ludger Paehler, Konstantinos Parasyris +6
Code is increasingly becoming a core data modality of modern machine learning research impacting not only the way we write code with conversational agents like OpenAI's ChatGPT, Go…