4 citations · 5 across the 4 of their papers we have counts for
4 papers
Imbalances in Neurosymbolic Learning: Characterization and Mitigating Strategies
Kaifu Wang, Efthymia Tsamoura, Dan Roth
We study one of the most popular problems in **neurosymbolic learning** (NSL), that of learning neural classifiers given only the result of applying a symbolic component to the…
On Regularization and Inference with Label Constraints
Kaifu Wang, Hangfeng He, Tin D. Nguyen +2
Prior knowledge and symbolic rules in machine learning are often expressed in the form of label constraints, especially in structured prediction problems. In this work, we compare…
On Learning Latent Models with Multi-Instance Weak Supervision
Kaifu Wang, Efthymia Tsamoura, Dan Roth
We consider a weakly supervised learning scenario where the supervision signal is generated by a transition function of labels associated with multiple input instances. We form…
Learnability with Indirect Supervision Signals
Kaifu Wang, Qiang Ning, Dan Roth
Learning from indirect supervision signals is important in real-world AI applications when, often, gold labels are missing or too costly. In this paper, we develop a unified theore…