Papers with approximating inference

1 papers
Benchmarking Approximate Inference Methods for Neural Structured Prediction (N19-1)

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Challenge: Structured prediction models often involve complex inference problems for which finding exact solutions is intractable.
Approach: They propose to perform gradient descent with respect to the output structure directly and train a neural network to perform inference.
Outcome: The proposed methods achieve better speed/accuracy/search error trade-off than gradient descent while being faster than exact inference at similar accuracy levels.

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