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Publication search results
found 11 matches
- 2020
- Tom Diethe, Oluwaseyi Feyisetan:
Preserving Privacy in Analyses of Textual Data. PrivateNLP@WSDM 2020: 1-3 - Oluwaseyi Feyisetan, Borja Balle:
Privacy-Preserving Textual Analysis via Calibrated Perturbations. PrivateNLP@WSDM 2020: 41-42 - Oluwaseyi Feyisetan, Borja Balle, Tom Diethe, Thomas Drake:
Calibrating Mechanisms for Privacy Preserving Text Analysis. PrivateNLP@WSDM 2020: 8-11 - Oluwaseyi Feyisetan, Tom Diethe, Thomas Drake:
Hyperbolic Embeddings for Preserving Privacy and Utility in Text. PrivateNLP@WSDM 2020: 39-40 - Vijayanta Jain, Sepideh Ghanavati:
Is It Possible to Preserve Privacy in the Age of AI? PrivateNLP@WSDM 2020: 32-36 - 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: 21-26 - 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: 12-20 - Robert Podschwadt, Daniel Takabi:
Classification of Encrypted Word Embeddings using Recurrent Neural Networks. PrivateNLP@WSDM 2020: 27-31 - Patricia Thaine, Gerald Penn:
Perfectly Privacy-Preserving AI What Is It and How Do We Achieve It? PrivateNLP@WSDM 2020: 4-7 - Patricia Thaine, Gerald Penn:
Perfectly Privacy-Preserving AI What Is It and How Do We Achieve It? PrivateNLP@WSDM 2020: 37-38 - Oluwaseyi Feyisetan, Sepideh Ghanavati, Oleg Rokhlenko, Patricia Thaine:
Proceedings of the PrivateNLP 2020: Workshop on Privacy in Natural Language Processing - Colocated with WSDM 2020, Houston, USA, Feb 7, 2020. CEUR Workshop Proceedings 2573, CEUR-WS.org 2020 [contents]
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