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06/06/2023
Towards Memory-Efficient Training for Extremely Large Output Spaces – Learning with 500k Labels on a Single Commodity GPU
In classification problems with large output spaces (up to millions of l...
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03/28/2023
Physics-guided adversarial networks for artificial digital image correlation data generation
Digital image correlation (DIC) has become a valuable tool in the evalua...
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10/29/2022
CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label Classification
Extreme Multi-label Text Classification (XMC) involves learning a classi...
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07/26/2022
On Missing Labels, Long-tails and Propensities in Extreme Multi-label Classification
The propensity model introduced by Jain et al. 2016 has become a standar...
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09/27/2021
Speeding-up One-vs-All Training for Extreme Classification via Smart Initialization
In this paper we show that a simple, data dependent way of setting the i...
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09/23/2021
Unbiased Loss Functions for Multilabel Classification with Missing Labels
This paper considers binary and multilabel classification problems in a ...
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07/01/2020