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cs.LG2025
Distributions In, Distributions Out: The Case for Soft-Label Training
Agamdeep Singh, Ashish Tiwari, Hosein Hasanbeig +1
Supervised classifiers output a distribution over classes but are typically trained against a single label obtained by collapsing multiple annotators into a majority vote. On tasks…
cs.LG2021
A Probabilistic Framework for Knowledge Graph Data Augmentation
Jatin Chauhan, Priyanshu Gupta, Pasquale Minervini
We present NNMFAug, a probabilistic framework to perform data augmentation for the task of knowledge graph completion to counter the problem of data scarcity, which can enhance the…