Adversarial Training Methods For Semi-Supervised Text Classification

Introduction This paper is the first work that applies adversarial training and virtual adversarial training to sequence models, and it greatly improved text classification tasks. In applying the adversarial training, this paper adopts distributed word representation, or word embedding, as the input, rather than the traditional one-hot representation. The reason lies in the fact that […]

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Kullback-Leibler Divergence Explained

Introduction This blog is an introduction on the KL-divergence, aka relative entropy. The blog gives a simple example for understand relative entropy, and therefore I will not attempt to re-write the authors words. What I will do, in addition to reading the blog (which can be found at https://www.countbayesie.com/blog/2017/5/9/kullback-leibler-divergence-explained), is try to convey some extra […]

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