398 citations · 2.8k across the 98 of their papers we have counts for
6 papers · 1 filter
Multilingual Relation Extraction using Compositional Universal Schema
Patrick Verga, David Belanger, Emma Strubell +2
Universal schema builds a knowledge base (KB) of entities and relations by jointly embedding all relation types from input KBs as well as textual patterns expressing relations from…
Structured Prediction Energy Networks
David Belanger, Andrew McCallum
We introduce structured prediction energy networks (SPENs), a flexible framework for structured prediction. A deep architecture is used to define an energy function of candidate la…
Compositional Vector Space Models for Knowledge Base Completion
Arvind Neelakantan, Benjamin Roth, Andrew McCallum
Knowledge base (KB) completion adds new facts to a KB by making inferences from existing facts, for example by inferring with high likelihood nationality(X,Y) from bornIn(X,Y). Mos…
Learning Dynamic Feature Selection for Fast Sequential Prediction
Emma Strubell, Luke Vilnis, Kate Silverstein +1
We present paired learning and inference algorithms for significantly reducing computation and increasing speed of the vector dot products in the classifiers that are at the heart…
Efficient Non-parametric Estimation of Multiple Embeddings per Word in Vector Space
Arvind Neelakantan, Jeevan Shankar, Alexandre Passos +1
There is rising interest in vector-space word embeddings and their use in NLP, especially given recent methods for their fast estimation at very large scale. Nearly all this work,…
Bethe Projections for Non-Local Inference
Luke Vilnis, David Belanger, Daniel Sheldon +1
Many inference problems in structured prediction are naturally solved by augmenting a tractable dependency structure with complex, non-local auxiliary objectives. This includes the…