In this paper, we analyze a recently proposed technique known as “self-normalization”, which introduces a regularization term in training to penalize log ...
In this paper, we analyze a recently proposed technique known as self-normalization'', which introduces a regularization term in training to penalize log ...
Jun 12, 2015 · In this paper, we analyze a recently proposed technique known as "self-normalization", which introduces a regularization term in training to ...
Calculation of the log-normalizer is a major computational obstacle in applica- tions of log-linear models with large output spaces. The problem of fast ...
This paper analyzes a recently proposed technique known as "self-normalization", which introduces a regularization term in training to penalize log ...
Jan 21, 2021 · Bibliographic details on On the Accuracy of Self-Normalized Log-Linear Models.
On the accuracy of self-normalized log-linear models. J Andreas, M Rabinovich, MI Jordan, D Klein. Advances in Neural Information Processing Systems 28, 2015.
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[PDF] When and why are log-linear models self-normalizing? - MIT
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Several techniques have recently been pro- posed for training “self-normalized” discrimi- native models. These attempt to find parameter.
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