We have presented a neural framework for generalized topic models to enable rapid exploration of models with covariates, interactions, and customized regularizers. We take advantage of sampling-based variational inference to develop a general algo...

In this paper we present a strong connection between non-malleable extractors and two-source extractors. First, we show that non-malleable extractors can be used to construct two-source extractors. If the non-malleable extractor works for small mi...

Overloading the Library Functions: It is not difficult to see that piecewise univariate functions can be implemented in our library.

We have proposed node-based learning of multiple Gaussian graphical models through the use of two convex formulations, perturbed-node joint graphical lasso and cohub node joint graphical lasso. These techniques are well-motivated by many real-worl...

We compare three generally-applicable strategies for translating out-of-vocabulary words, none of which rely on any language-specific resources or typological assumptions beyond the presence of subword units. Integrating these OOV translators into...