Kernel Principal Component Analysis

In this paper, we introduce a new semi-supervised learning model for word sense disambiguation based on Kernel Prin- cipal Component Analysis (KPCA), with experiments showing that it can further improve …...

This paper proposes a variability normaliza- tion algorithm to reduce the variability be- tween intra-topic documents for topic classi- fication. Firstly, an optimization problem is constructed based on linear variability …...

AbstractBolukbasi et al. (2016) presents one of the first gender bias mitigation techniques for word embeddings. Their method takes pre-trained word embeddings as input and attempts to isolate a linear …...