Damien Teney

Predicting is not Understanding: Recognizing and Addressing Underspecification in Machine Learning

2022 · arXiv (Cornell University)

Machine learning (ML) models are typically optimized for their accuracy on a given dataset. However, this predictive criterion rarely captures all desirable properties of a model, in particular how well it matches a domain expert's …

Leveraging Diffusion Disentangled Representations to Mitigate Shortcuts in Underspecified Visual Tasks

2023 · arXiv (Cornell University)

Spurious correlations in the data, where multiple cues are predictive of the target labels, often lead to shortcut learning phenomena, where a model may rely on erroneous, easy-to-learn, cues while ignoring reliable ones. In this …

OOD-Chameleon: Is Algorithm Selection for OOD Generalization Learnable?

2024 · arXiv (Cornell University)

Out-of-distribution (OOD) generalization is challenging because distribution shifts come in many forms. Numerous algorithms exist to address specific settings, but choosing the right training algorithm for the right dataset without trial and error is difficult. …