13 citations · 20 across the 11 of their papers we have counts for
3 papers · 1 filter
Why Fine-grained Labels in Pretraining Benefit Generalization?
Guan Zhe Hong, Yin Cui, Ariel Fuxman +2
Recent studies show that pretraining a deep neural network with fine-grained labeled data, followed by fine-tuning on coarse-labeled data for downstream tasks, often yields better…
Agile Modeling: From Concept to Classifier in Minutes
Otilia Stretcu, Edward Vendrow, Kenji Hata +15
The application of computer vision to nuanced subjective use cases is growing. While crowdsourcing has served the vision community well for most objective tasks (such as labeling a…
CARLS: Cross-platform Asynchronous Representation Learning System
Chun-Ta Lu, Yun Zeng, Da-Cheng Juan +13
In this work, we propose CARLS, a novel framework for augmenting the capacity of existing deep learning frameworks by enabling multiple components -- model trainers, knowledge make…