| Privacy-and utility-preserving textual analysis via calibrated multivariate perturbations O Feyisetan, B Balle, T Drake, T Diethe Proceedings of the 13th international conference on web search and data …, 2020 | 138 | 2020 |
| Leveraging hierarchical representations for preserving privacy and utility in text O Feyisetan, T Diethe, T Drake 2019 IEEE International Conference on Data Mining (ICDM), 210-219, 2019 | 86 | 2019 |
| Leveraging crowdsourcing data for deep active learning an application: Learning intents in alexa J Yang, T Drake, A Damianou, Y Maarek Proceedings of the 2018 World Wide Web Conference, 23-32, 2018 | 74 | 2018 |
| Privacy and intent-preserving redaction for text utterance data T Drake, O Feyisetan, B de Balle Pigem, T Diethe US Patent 11,024,299, 2021 | 13 | 2021 |
| Privacy-preserving active learning on sensitive data for user intent classification O Feyisetan, T Drake, B Balle, T Diethe arXiv preprint arXiv:1903.11112, 2019 | 11 | 2019 |
| Preserving privacy in analyses of textual data T Diethe, O Feyisetan, B Balle, T Drake | 7 | 2020 |
| Data-preserving text redaction for text utterance data T Drake, O Feyisetan, T Diethe US Patent 11,308,945, 2022 | 1 | 2022 |
| Calibrating Mechanisms for Privacy Preserving Text Analysis. O Feyisetan, B Balle, T Diethe, T Drake PrivateNLP@ WSDM, 8-11, 2020 | 1 | 2020 |
| Hyperbolic Embeddings for Preserving Privacy and Utility in Text. O Feyisetan, T Diethe, T Drake PrivateNLP@ WSDM, 39-40, 2020 | | 2020 |
Oluwaseyi FeyisetanAmazon ResearchVerified email at amazon.com
