Dropping the top-k most important instances in a bag regularizes MIL training and improves classification; the proposed MIL-Dropout applies this idea to existing MIL aggregators.
Timemil: advancing multivariate time series classification via a time-aware multiple instance learning
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How Effective Can Dropout Be in Multiple Instance Learning ?
Dropping the top-k most important instances in a bag regularizes MIL training and improves classification; the proposed MIL-Dropout applies this idea to existing MIL aggregators.