Kartik Ahuja

SAND-mask: An Enhanced Gradient Masking Strategy for the Discovery of Invariances in Domain Generalization

2021 · arXiv (Cornell University)

A major bottleneck in the real-world applications of machine learning models is their failure in generalizing to unseen domains whose data distribution is not i.i.d to the training domains. This failure often stems from learning …

Model Ratatouille: Recycling Diverse Models for Out-of-Distribution Generalization

2022 · arXiv (Cornell University)

Foundation models are redefining how AI systems are built. Practitioners now follow a standard procedure to build their machine learning solutions: from a pre-trained foundation model, they fine-tune the weights on the target task of …