InfoMax selects a training subset by solving a discrete quadratic program that balances sample importance scores against pairwise similarity penalties, and reports state-of-the-art pruning results across three deep learning tasks.
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Data Pruning by Information Maximization
InfoMax selects a training subset by solving a discrete quadratic program that balances sample importance scores against pairwise similarity penalties, and reports state-of-the-art pruning results across three deep learning tasks.