Papers by Amirmohammad Rooshenas

2 papers
Training Structured Prediction Energy Networks with Indirect Supervision (N18-2)

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Challenge: a new rank-based training method for structured prediction energy networks is proposed . structured prediction is important in many domains, including computer vision, computational biology and natural language processing.
Approach: They propose a rank-based training method for structured prediction energy networks . they use a scoring function defined with domain knowledge to train the models .
Outcome: The proposed method minimizes ranking violation of the sampled structures with respect to a scalar scoring function defined with domain knowledge.
Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based Models (2021.acl-long)

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Challenge: Autoregressive neural machine translation (NMT) uses a tractable likelihood computation and efficient sampling.
Approach: They propose to use an energy-based model to mimic the behavior of the task measure and use it to train an energy based re-ranking algorithm.
Outcome: The proposed model improves on the samples drawn from the NMT with a higher BLEU score than the experimental model and the energy-based re-ranking algorithm.

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