Tag: coreset-selection (3 references)
DeepCore: A Comprehensive Library for Coreset Selection in Deep Learning
Comprehensive library and empirical study of coreset selection methods for deep learning, finding that random selection remains a strong baseline across many settings.
Coresets for Data-efficient Training of Machine Learning Models
Introduces CRAIG (Coresets for Accelerating Incremental Gradient descent), selecting subsets that approximate full gradient for 2-3x training speedups while maintaining performance.
Active Learning for Convolutional Neural Networks: A Core-Set Approach
Defines active learning as core-set selection, choosing points such that a model trained on the subset is competitive for remaining data. Provides theoretical bounds via k-Center problem.