Is Fairness Only Metric Deep? Evaluating and Addressing Subgroup Gaps in Deep Metric Learning

International Conference on Learning Representations
Kimia Hamidieh
Kimia Hamidieh

Kimia is a PhD student at University of Toronto and Vector Institute visiting MIT. Her research focuses on understanding how self-supervised pre-training strategies represent data to build models that generalize well out-of-distribution, and developing methods that enable efficient and reliable adaptation. She is also interested in leveraging properties of large models for reasoning and robustness to distribution shifts.