Search papers, labs, and topics across Lattice.
Affiliation:
2
0
2
Informative missing labels can significantly enhance classification accuracy by providing insights into uncertainty, leading to reduced expected error rates in semi-supervised settings.
Informative label missingness can lead to lower classification risk in multiclass settings, defying the conventional wisdom that more labels always yield better performance.
