CRISP: Scalable Importance-Stratified Coresets for Imbalanced Tabular Learning
cs.LG
Submitted: 2026-09-22
Updated: 2026-09-22
Terminology
Sources
- Selection via Proxy: Efficient Data Selection for Deep Learning
- GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training
- GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning
- An Instance Selection Algorithm for Big Data in High imbalanced datasets based on LSH
- Coresets for Data-efficient Training of Machine Learning Models
- Deep Learning on a Data Diet: Finding Important Examples Early in Training
- Estimating Training Data Influence by Tracing Gradient Descent
- CriteoPrivateAds: A Real-World Bidding Dataset to Design Private Advertising Systems
- Active Learning for Convolutional Neural Networks: A Core-Set Approach
- Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics
- An Empirical Study of Example Forgetting during Deep Neural Network Learning
- FLAML: A Fast and Lightweight AutoML Library
- Coverage-centric Coreset Selection for High Pruning Rates
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