11 citations · 11 across the 1 of their papers we have counts for
3 papers
An Empirical Investigation of Beam-Aware Training in Supertagging
Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon
Structured prediction is often approached by training a locally normalized model with maximum likelihood and decoding approximately with beam search. This approach leads to mismatc…
Towards modular and programmable architecture search
Renato Negrinho, Darshan Patil, Nghia Le +3
Neural architecture search methods are able to find high performance deep learning architectures with minimal effort from an expert. However, current systems focus on specific use-…
Learning Beam Search Policies via Imitation Learning
Renato Negrinho, Matthew R. Gormley, Geoffrey J. Gordon
Beam search is widely used for approximate decoding in structured prediction problems. Models often use a beam at test time but ignore its existence at train time, and therefore do…