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This paper tackles one of the greatest limitations in Machine Learning: Data Scarcity.
“EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks”
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Silvia Gennari, Maryellen MacDonald, Bradley Postle and Mark Seidenberg · 2007
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“Alternate equivalent substitutes: Recognition of synonyms using word vectors”, 2013
Tri Dao, Sam Keller and Alborz Bejnood · 2013
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“Distributed representations of words and phrases and their compositionality”
Tomas Mikolov et al · 2013
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“Glove: Global vectors for word representation”
Jeffrey Pennington, Richard Socher and Christopher. Manning · 2014
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“Character-level Convolutional Networks for Text Classification”
Xiang Zhang, Junbo Zhao and Yann LeCun · 2015
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“Do We Need More Training Data?”
Xiangxin Zhu, Carl Vondrick, Charless. Fowlkes and Deva Ramanan · 2015
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“Improving Neural Machine Translation Models with Monolingual Data”
Rico Sennrich, Barry Haddow and Alexandra Birch · 2016
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“ImageNet Classification with Deep Convolutional Neural Networks”
Alex Krizhevsky, Ilya Sutskever and Geoffrey. Hinton · 2017
Cited alongside, same era.
“English conversational telephone speech recognition by humans and machines”
George Saon et al · 2017
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“Revisiting Unreasonable Effectiveness of Data in Deep Learning Era”
Chen Sun, Abhinav Shrivastava, Saurabh Singh and Abhinav Gupta · 2017
Cited alongside, same era.
Ashish Vaswani et al · 2017
Cited alongside, same era.
“Attention is all you need”
Ashish Vaswani et al · 2017
Cited alongside, same era.
“Fine-tuned Language Models for Text Classification”
Jeremy Howard and Sebastian Ruder · 2018
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“Contextual augmentation: Data augmentation by words with paradigmatic relations”
Sosuke Kobayashi · 2018
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“State-of-the-Art Speech Recognition Using Multi-Stream Self-Attention With Dilated 1D Convolutions”
Kyu Han, Ramon Prieto, Kaixing Wu and Tao Ma · 2019
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“BPE-Dropout: Simple and Effective Subword Regularization”
Ivan Provilkov, Dmitrii Emelianenko and Elena Voita · 2019
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“Megatron-lm: Training multi-billion parameter language models using gpu model parallelism”
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Jacob Devlin, Ming-Wei Chang, Kenton Lee and Kristina Toutanova · 2018
Cited alongside, same era.
“Understanding back-translation at scale”
Sergey Edunov, Myle Ott, Michael Auli and David Grangier · 2018
Cited alongside, same era.
“CH 2: SVM Theory”, https://bit.ly/2KsERg2
Cited in the paper.
“Google Translate Setup: Quickstart Guide”, https://cloud.google.com/translate/docs/basic/setup-basic
Cited in the paper.
“List of languages by number of native speakers”, https://en.wikipedia.org/wiki/List_of_languages_by_number_of_native_speakers
Cited in the paper.
“Logisitic Regression: ML Cheatsheet”, https://ml-cheatsheet.readthedocs.io/en/latest/logistic_regression.html
Cited in the paper.
“LSTM”, https://skymind.ai/wiki/lstm
Cited in the paper.
Mohammad Shoeybi et al · 2019
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“Self-training with Noisy Student improves ImageNet classification”
Qizhe Xie, Eduard Hovy, Minh-Thang Luong and Quoc Le · 2019
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“Object-Contextual Representations for Semantic Segmentation”
Yuhui Yuan, Xilin Chen and Jingdong Wang · 2019
Later among the works it cites.