PrivateNLP@WSDM

Keyphrases

Publications

2020

Tom Diethe, Oluwaseyi Feyisetan
Preserving Privacy in Analyses of Textual Data. PrivateNLP@WSDM (2020)
Patricia Thaine, Gerald Penn
Perfectly Privacy-Preserving AI What Is It and How Do We Achieve It? PrivateNLP@WSDM (2020)
Levi Melnick, Hussein Elmessilhy, Vassilis Polychronopoulos, Gilsinia Lopez, Yuancheng Tu, Omar Zia Khan, Ye-Yi Wang, Chris Quirk
Privacy-Aware Personalized Entity Representations for Improved User Understanding. PrivateNLP@WSDM (2020)
Patricia Thaine, Gerald Penn
Perfectly Privacy-Preserving AI What Is It and How Do We Achieve It? PrivateNLP@WSDM (2020)
A. K. M. Nuhil Mehdy, Hoda Mehrpouyan
A User-Centric and Sentiment Aware Privacy-Disclosure Detection Framework based on Multi-input Neural Network. PrivateNLP@WSDM (2020)
Oluwaseyi Feyisetan, Tom Diethe, Thomas Drake
Hyperbolic Embeddings for Preserving Privacy and Utility in Text. PrivateNLP@WSDM (2020)
Robert Podschwadt, Daniel Takabi
Classification of Encrypted Word Embeddings using Recurrent Neural Networks. PrivateNLP@WSDM (2020)
Vijayanta Jain, Sepideh Ghanavati
Is It Possible to Preserve Privacy in the Age of AI? PrivateNLP@WSDM (2020)
Oluwaseyi Feyisetan, Borja Balle, Tom Diethe, Thomas Drake
Calibrating Mechanisms for Privacy Preserving Text Analysis. PrivateNLP@WSDM (2020)
Oluwaseyi Feyisetan, Borja Balle
Privacy-Preserving Textual Analysis via Calibrated Perturbations. PrivateNLP@WSDM (2020)

volume 2573, 2020

Proceedings of the PrivateNLP 2020: Workshop on Privacy in Natural Language Processing - Colocated with WSDM 2020, Houston, USA, Feb 7, 2020. PrivateNLP@WSDM 2573 (2020)