Papers › BWS: Best Window Selection Based on Sample Scores for Data Pruning across Broad Ranges

BWS: Best Window Selection Based on Sample Scores for Data Pruning across Broad Ranges

5 Jun 2024arXiv:2406.03057archive 2025-07-28

Hoyong Choi, Nohyun Ki, Hye Won Chung

Data subset selection aims to find a smaller yet informative subset of a large dataset that can approximate the full-dataset training, addressing challenges associated with training neural networks on large-scale datasets. However, existing methods tend to specialize in either high or low selection ratio regimes, lacking a universal approach that consistently achieves competitive performance across a broad range of selection ratios. We introduce a universal and efficient data subset selection method, Best Window Selection (BWS), by proposing a method to choose the best window subset from samples ordered based on their difficulty scores. This approach offers flexibility by allowing the choice of window intervals that span from easy to difficult samples. Furthermore, we provide an efficient mechanism for selecting the best window subset by evaluating its quality using kernel ridge regression. Our experimental results demonstrate the superior performance of BWS compared to other baselines across a broad range of selection ratios over datasets, including CIFAR-10/100 and ImageNet, and the scenarios involving training from random initialization or fine-tuning of pre-trained models.

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BasicCNN NohyunKi/BWS/model/cnn.py official repository ran no licence file found · pointer only · 5da00b10b4927698 · report
BasicFC NohyunKi/BWS/model/fc.py official repository ran no licence file found · pointer only · fe1cc23c87d33225 · report
ConvNet NohyunKi/BWS/model/convnet.py official repository ran no licence file found · pointer only · 2dfd0d1de2e58612 · report
DenseNetBC_100_12 NohyunKi/BWS/model/densenet.py official repository ran no licence file found · pointer only · e8d04a55a8d31937 · report
DenseNetBC_190_40 NohyunKi/BWS/model/densenet.py official repository ran no licence file found · pointer only · 01afd1b412e19970 · report
DenseNetBC_250_24 NohyunKi/BWS/model/densenet.py official repository ran no licence file found · pointer only · 2128df9138fd8f37 · report
EfficientNetB0 NohyunKi/BWS/model/efficientnet.py official repository ran no licence file found · pointer only · c52ea9ddb582c0f6 · report
ResNet18 NohyunKi/BWS/model/resnet.py official repository ran no licence file found · pointer only · af713fc888bdc5de · report
ResNet34 NohyunKi/BWS/model/resnet.py official repository ran no licence file found · pointer only · 38d8a6134f95e3ec · report
ResNet50 NohyunKi/BWS/model/resnet.py official repository ran no licence file found · pointer only · 49947d532c030d74 · report
drop_connect NohyunKi/BWS/model/efficientnet.py official repository ran fingerprinted no licence file found · pointer only · 4304a326c593f8db · report
get_pruning_window NohyunKi/BWS/experiment/pruning_window_sliding.py official repository ran no licence file found · pointer only · b3ff683d979be1e9 · report
get_window nohyunki/bws/experiment/pruning_measure.py official repository ran · our draft was wrong no licence file found · pointer only · bde2fd407de25a81 · report
swish NohyunKi/BWS/model/efficientnet.py official repository ran fingerprinted no licence file found · pointer only · 8737c82de631cffc · report

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