36 citations · 76 across the 13 of their papers we have counts for
5 papers · 1 filter
Deconstructing word embedding algorithms
Kian Kenyon-Dean, Edward Newell, Jackie Chi Kit Cheung
Word embeddings are reliable feature representations of words used to obtain high quality results for various NLP applications. Uncontextualized word embeddings are used in many NL…
Learning Efficient Task-Specific Meta-Embeddings with Word Prisms
Jingyi He, KC Tsiolis, Kian Kenyon-Dean +1
Word embeddings are trained to predict word cooccurrence statistics, which leads them to possess different lexical properties (syntactic, semantic, etc.) depending on the notion of…
Deconstructing and reconstructing word embedding algorithms
Edward Newell, Kian Kenyon-Dean, Jackie Chi Kit Cheung
Uncontextualized word embeddings are reliable feature representations of words used to obtain high quality results for various NLP applications. Given the historical success of wor…
Word Embedding Algorithms as Generalized Low Rank Models and their Canonical Form
Kian Kenyon-Dean
Word embedding algorithms produce very reliable feature representations of words that are used by neural network models across a constantly growing multitude of NLP tasks. As such,…
Resolving Event Coreference with Supervised Representation Learning and Clustering-Oriented Regularization
Kian Kenyon-Dean, Jackie Chi Kit Cheung, Doina Precup
We present an approach to event coreference resolution by developing a general framework for clustering that uses supervised representation learning. We propose a neural network ar…