T
Tomas Mikolov
Researcher at Facebook
Publications - 94
Citations - 122079
Tomas Mikolov is an academic researcher from Facebook. The author has contributed to research in topics: Language model & Recurrent neural network. The author has an hindex of 49, co-authored 94 publications receiving 104987 citations. Previous affiliations of Tomas Mikolov include Microsoft & Google.
Papers
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Proceedings Article
Distributed Representations of Sentences and Documents
Quoc V. Le,Tomas Mikolov +1 more
TL;DR: Paragraph Vector is an unsupervised algorithm that learns fixed-length feature representations from variable-length pieces of texts, such as sentences, paragraphs, and documents, and its construction gives the algorithm the potential to overcome the weaknesses of bag-of-words models.
Proceedings Article
Recurrent neural network based language model
TL;DR: Results indicate that it is possible to obtain around 50% reduction of perplexity by using mixture of several RNN LMs, compared to a state of the art backoff language model.
Proceedings ArticleDOI
Bag of Tricks for Efficient Text Classification
TL;DR: FastText as mentioned in this paper explores a simple and efficient baseline for text classification, which is often on par with deep learning classifiers in terms of accuracy and many orders of magnitude faster for training and evaluation.
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On the difficulty of training Recurrent Neural Networks
TL;DR: This paper proposes a gradient norm clipping strategy to deal with exploding gradients and a soft constraint for the vanishing gradients problem and validates empirically the hypothesis and proposed solutions.
Posted Content
Distributed Representations of Sentences and Documents
Quoc V. Le,Tomas Mikolov +1 more
TL;DR: The authors proposed paragraph vector, an unsupervised algorithm that learns fixed-length feature representations from variable-length pieces of texts, such as sentences, paragraphs, and documents, and achieved new state-of-the-art results on several text classification and sentiment analysis tasks.