Meeting #132: [Online; 15:00] Geometric Dataset Distances via Optimal Transport

[Hrant Khachatrian]

Hi everyone,

This week Davit Karamyan (Krisp / PhD student at RAU) will present a NeurIPS 2020 paper from Microsoft Research on another distance measure between datasets. The serious advantage of this method is that it is model-agnostic and does not require training. 

Link to the paper: https://arxiv.org/abs/2002.02923 

See you on Saturday at 15.00 on Zoom: https://us02web.zoom.us/j/84008166778?pwd=RkVjazZkS3JiM2JRS3dCZTVVdmM1dz09 

Best,

Hrant

[Adam Bittlingmayer]

Is it specific to image datasets, natural language datasets, both or something else?

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Adam Bittlingmayer

CEO, ModelFront

Translation risk prediction

[David Karamyan]

It is general distance. It can be applied to images and text datasets as well.

пт, 11 февр. 2022 г. в 13:51, Adam Bittlingmayer <ad...@modelfront.com>:

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