Jan 26, 2023 � We propose SoftMatch to overcome the trade-off by maintaining both high quantity and high quality of pseudo-labels during training, effectively exploiting the�...
Feb 1, 2023 � To this end, we propose SoftMatch to overcome the trade-off by maintaining both high quantity and high quality of pseudo-labels during training,�...
Official repo for SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-Supervised Learning, accepted by ICLR 2023.
The critical challenge of Semi-Supervised Learning (SSL) is how to effectively leverage the limited labeled data and massive unlabeled data to improve the.
Jan 26, 2023 � To this end, we propose SoftMatch to overcome the trade-off by maintaining both high quantity and high quality of pseudo-labels during training,�...
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Sep 30, 2023 � Bibliographic details on SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning.
Mar 15, 2023 � To this end, we propose SoftMatch to overcome the trade-off by maintaining both high quantity and high quality of pseudo-labels during training,�...
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... SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised ... classification semi-supervised-learning audio-classification low-resource�...
SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning � 4 code implementations • 26 Jan 2023 • Hao Chen, Ran Tao, Yue Fan, Yidong�...