most citedHERA: Partial Label Learning by Combining Heterogeneous Loss with Sparse and Low-Rank Regularization

3 citations · 3 across the 1 of their papers we have counts for

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1 paper

cs.LG2019★ 3 cited

HERA: Partial Label Learning by Combining Heterogeneous Loss with Sparse and Low-Rank Regularization

Gengyu Lyu, Songhe Feng, Yi Jin +3

Partial Label Learning (PLL) aims to learn from the data where each training instance is associated with a set of candidate labels, among which only one is correct. Most existing m…