8 citations · 9 across the 2 of their papers we have counts for
3 papers
Learning Better Internal Structure of Words for Sequence Labeling
Yingwei Xin, Ethan Hart, Vibhuti Mahajan +1
Character-based neural models have recently proven very useful for many NLP tasks. However, there is a gap of sophistication between methods for learning representations of sentenc…
Paraphrase-Supervised Models of Compositionality
Avneesh Saluja, Chris Dyer, Jean-David Ruvini
Compositional vector space models of meaning promise new solutions to stubborn language understanding problems. This paper makes two contributions toward this end: (i) it uses auto…
Probabilistic Combination of Classifier and Cluster Ensembles for Non-transductive Learning
Ayan Acharya, Eduardo R. Hruschka, Joydeep Ghosh +2
Unsupervised models can provide supplementary soft constraints to help classify new target data under the assumption that similar objects in the target set are more likely to share…