Fetching the paper…
Reading the bibliography…
This article deals with adversarial attacks towards deep learning systems for Natural Language Processing (NLP), in the context of privacy protection.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Latent dirichlet allocation
David M. Blei, Andrew Y. Ng, and Michael I. Jordan. 2003 · 2003
Earlier work this paper cites.
Ranking a stream of news
Gianna M. Del Corso, Antonio Gullí, and Francesco Romani. 2005 · 2005
Earlier work this paper cites.
Differential privacy
Cynthia Dwork. 2006 · 2006
Earlier work this paper cites.
Effects of age and gender on blogging
Jonathan Schler, Moshe Koppel, Shlomo Argamon, and James Pennebaker. 2006 · 2006
Earlier work this paper cites.
Natural Language Processing with Python , 1st edition
Steven Bird, Ewan Klein, and Edward Loper. 2009 · 2009
Earlier work this paper cites.
Age prediction in blogs: A study of style, content, and online behavior in pre- and post-social media generations
Sara Rosenthal and Kathleen McKeown. 2011 · 2011
Earlier work this paper cites.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2014 · 2014
Earlier work this paper cites.
Demographic factors improve classification performance
Dirk Hovy. 2015 · 2015
Cited alongside, same era.
User review sites as a resource for large-scale sociolinguistic studies
Dirk Hovy, Anders Johannsen, and Anders Søgaard. 2015 · 2015
Cited alongside, same era.
Tagging performance correlates with author age
Dirk Hovy and Anders Søgaard. 2015 · 2015
Cited alongside, same era.
An analysis of the user occupational class through twitter content
Daniel Preoţiuc-Pietro, Vasileios Lampos, and Nikolaos Aletras. 2015 · 2015
Cited alongside, same era.
Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
Cited alongside, same era.
Deep learning with differential privacy
Martin Abadi, Andy Chu, Ian Goodfellow, H. Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang. 2016 · 2016
Cited alongside, same era.
Text classification improved by integrating bidirectional lstm with two-dimensional max pooling
Peng Zhou, Zhenyu Qi, Suncong Zheng, Jiaming Xu, Hongyun Bao, and Bo Xu. 2016 · 2016
Later among the works it cites.
Meng Li, Liangzhen Lai, Naveen Suda, Vikas Chandra, and David Z. Pan. 2017 · 2017
Later among the works it cites.
Dynet: The dynamic neural network toolkit
Graham Neubig, Chris Dyer, Yoav Goldberg, Austin Matthews, Waleed Ammar, Antonios Anastasopoulos, Miguel Ballesteros, David Chiang, Daniel Clothiaux, Trevor Cohn, Kevin Duh, Manaal Faruqui, Cynthia Gan, Dan Garrette, Yangfeng Ji, Lingpeng Kong, Adhiguna Kuncoro, Gaurav Kumar, Chaitanya Malaviya, Paul Michel, Yusuke Oda, Matthew Richardson, Naomi Saphra, Swabha Swayamdipta, and Pengcheng Yin. 2017 · 2017
Later among the works it cites.
Multilingual hierarchical attention networks for document classification
Nikolaos Pappas and Andrei Popescu-Belis. 2017 · 2017
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
The social impact of natural language processing
Dirk Hovy and Shannon L. Spruit. 2016 · 2016
Cited alongside, same era.
Semi-supervised knowledge transfer for deep learning from private training data
Nicolas Papernot, Martín Abadi, Úlfar Erlingsson, Ian J. Goodfellow, and Kunal Talwar. 2016 · 2016
Cited alongside, same era.
Attention-based LSTM for aspect-level sentiment classification
Yequan Wang, Minlie Huang, Xiaoyan Zhu, and Li Zhao. 2016 · 2016
Cited alongside, same era.
The secret sharer: Measuring unintended neural network memorization & extracting secrets
Nicholas Carlini, Chang Liu, Jernej Kos, Úlfar Erlingsson, and Dawn Song. 2018 · 2018
Closest in time.
Towards robust and privacy-preserving text representations
Yitong Li, Timothy Baldwin, and Trevor Cohn. 2018 · 2018
Closest in time.
Scalable Private Learning with PATE
Nicolas Papernot, Shuang Song, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, and Úlfar Erlingsson. 2018 · 2018
Closest in time.
Locally Private Bayesian Inference for Count Models
Aaron Schein, Zhiwei Steven Wu, Mingyuan Zhou, and Hanna Wallach. 2018 · 2018
Closest in time.