Low-dimensional vector representations are widely used as stand-ins for the text of words, sentences, and entire documents. These embeddings are used to identify similar words or make predictions about documents. In this work, we consider embeddings for social media users and demonstrate that these can be used to identify users who behave similarly or to predict attributes of users. In order to...

BACKGROUND Although an attentional bias for threat has been implicated in generalized anxiety disorder (GAD), evidence supporting such a bias has been inconsistent. This study examines whether exposure to different emotional content modulates attention disengagement and impairs the perception of subsequently presented nonemotional targets in GAD. METHODS Patients with GAD (n = 30) and control...

The paper describes experiments on estimating emotion intensity in tweets using a generalized regressor system. The system combines lexical, syntactic and pretrained word embedding features, trains them on general regressors and finally combines the best performing models to create an ensemble. The proposed system stood 3rd out of 22 systems in the leaderboard of WASSA-2017 Shared Task on Emoti...

The properties of the metric topology on infinite and finite sets are analyzed. We answer whether finite metric spaces hold interest in algebraic topology, and how this result is generalized to pseudometric spaces through the Kolmogorov quotient. Embedding into Lebesgue spaces is analyzed, with special attention for Hilbert spaces, `p, and EN .

We study continuity envelopes in spaces of generalized smoothness B ,N p,q (R n) and F σ ,N p,q (R n). The results are applied in proving sharp embedding assertions in some limiting situations. © 2008 Elsevier Inc. All rights reserved.

We present embeddings of generalized ladders as subgraphs into the hypercube. By embedding caterpillars into ladders, we obtain embeddings of caterpillars into the hypercube. In this way we obtain almost all known results concerning the embeddings of caterpillars into the hypercube. In addition we construct embeddings for some new types of caterpillars.

When a symmetric, positive, isomorphism between a reeexive Banach space (that is densely and compactly embedded in a Hilbert space) and its dual varies smoothly over a Banach space, its eigenvalues vary in a Lipschitz manner. We calculate the generalized gradient of the extreme eigenvalues at an arbitrary crossing. We apply this to the generalized gradient, with respect to a coeecient in an ell...