5.16组会笔记
Published:
Weak Supervision
熵 -> uniform distribution \(-\sum^i_m q_i \, log \, d_i ??\) Self-Training/Self-Supervised
Relieve Bias ?
EM optimization(similarity based loss + MIL/hinge loss/VAE)
Get higher-level supervision over unlabeled data from SMEs:
启发式规则
Distant Supervision, Constraints, Expected Distribution, Invariances.
External Knowledge
Label-free EMNLP 2018
Based on TransE pretrianed embedding, start entity + sentence embedding(predicted relation vector from neural model) == end entity