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cs.IR2019
Topic Modeling with Wasserstein Autoencoders
Feng Nan, Ran Ding, Ramesh Nallapati +1
We propose a novel neural topic model in the Wasserstein autoencoders (WAE) framework. Unlike existing variational autoencoder based models, we directly enforce Dirichlet prior on…
cs.IR2019★ 16 cited
Passage Ranking with Weak Supervision
Peng Xu, Xiaofei Ma, Ramesh Nallapati +1
In this paper, we propose a \textit{weak supervision} framework for neural ranking tasks based on the data programming paradigm \citep{Ratner2016}, which enables us to leverage mul…