Coreset Selection

HyperCore: Coreset Selection under Noise via Hypersphere Models
We present HyperCore, a lightweight adaprive coreset selection framework designed for noisy environments. HyperCore utilizes per class hypersphere models and adaptively selects pruning thresholds.
Brian Bernhard Moser, Arundhati Shanbhag, Tobias Christian Nauen, Stanislav Frolov, Federico Raue, Joachim Folz, Andreas Dengel
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HyperCore: Coreset Selection under Noise via Hypersphere Models
SubZeroCore: A Submodular Approach with Zero Training for Coreset Selection
We introduce SubZeroCore, a novel, training-free coreset selection method that integrates submodular coverage and density into a single, unified objective.
Brian Bernhard Moser, Tobias Christian Nauen, Arundhati Shanbhag, Federico Raue, Stanislav Frolov, Joachim Folz, Andreas Dengel
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SubZeroCore: A Submodular Approach with Zero Training for Coreset Selection