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Eva Dyer

2 accepted papers

2021

Making transport more robust and interpretable by moving data through a small number of anchor points

ICML 2021spotlight

Optimal transport (OT) is a widely used technique for distribution alignment, with applications throughout the machine learning, graphics, and vision communities. Without any additional structural assumptions on transport, however, OT can be fragile to outliers or noise, especially in high dimension…

2019

Hierarchical Optimal Transport for Multimodal Distribution Alignment

NeurIPS 2019poster

In many machine learning applications, it is necessary to meaningfully aggregate, through alignment, different but related datasets. Optimal transport (OT)-based approaches pose alignment as a divergence minimization problem: the aim is to transform a source dataset to match a target dataset using t…