Brandon M. Stewart

Also published as: Brandon Stewart


2018

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A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors
Mikhail Khodak | Nikunj Saunshi | Yingyu Liang | Tengyu Ma | Brandon Stewart | Sanjeev Arora
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Motivations like domain adaptation, transfer learning, and feature learning have fueled interest in inducing embeddings for rare or unseen words, n-grams, synsets, and other textual features. This paper introduces a la carte embedding, a simple and general alternative to the usual word2vec-based approaches for building such representations that is based upon recent theoretical results for GloVe-like embeddings. Our method relies mainly on a linear transformation that is efficiently learnable using pretrained word vectors and linear regression. This transform is applicable on the fly in the future when a new text feature or rare word is encountered, even if only a single usage example is available. We introduce a new dataset showing how the a la carte method requires fewer examples of words in context to learn high-quality embeddings and we obtain state-of-the-art results on a nonce task and some unsupervised document classification tasks.

2015

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TopicCheck: Interactive Alignment for Assessing Topic Model Stability
Jason Chuang | Margaret E. Roberts | Brandon M. Stewart | Rebecca Weiss | Dustin Tingley | Justin Grimmer | Jeffrey Heer
Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

2013

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Learning to Extract International Relations from Political Context
Brendan O’Connor | Brandon M. Stewart | Noah A. Smith
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)