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Towards better substitution-based word sense induction
This work extends the previous method to support a dynamic rather than a fixed number of clusters as supported by other prominent methods, and proposes a method for interpreting the resulting clusters by associating them with their most informative substitutes. Expand
Word Sense Induction with Neural biLM and Symmetric Patterns
The combination of the RNN-LM and the dynamic symmetric patterns results in strong substitute vectors for WSI, allowing to surpass the current state-of-the-art on the SemEval 2013 WSI shared task by a large margin. Expand
Bootstrapping Relation Extractors using Syntactic Search by Examples
This work proposes a process for bootstrapping training datasets which can be performed quickly by non-NLP-experts and takes advantage of search engines over syntactic-graphs to obtain positive examples by searching for sentences that are syntactically similar to user input examples. Expand
A simple geometric proof for the benefit of depth in ReLU networks
A sequence of classification problems indexed by m such that for any fixed depth rectified network there exist an m above which classifying problem m correctly requires exponential number of parameters, and a concrete neural network with linear depth and small constant width is presented. Expand