Oluwaseyi Feyisetan

According to our database, Oluwaseyi Feyisetan authored at least 29 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Fast Training Dataset Attribution via In-Context Learning.

Milad Fotouhi, Mohammad Taha Bahadori, Oluwaseyi Feyisetan, Payman Arabshahi, David Heckerman

CoRR, 2024

2023

TEM: High Utility Metric Differential Privacy on Text.

Ricardo Silva Carvalho, Theodore Vasiloudis, Oluwaseyi Feyisetan, Ke Wang

Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

2022

Reconstructing Test Labels from Noisy Loss Functions.

Abhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

TEM: High Utility Metric Differential Privacy on Text.

Ricardo Silva Carvalho, Theodore Vasiloudis, Oluwaseyi Feyisetan

CoRR, 2021

BRR: Preserving Privacy of Text Data Efficiently on Device.

Ricardo Silva Carvalho, Theodore Vasiloudis, Oluwaseyi Feyisetan

CoRR, 2021

On Codomain Separability and Label Inference from (Noisy) Loss Functions.

Abhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier

CoRR, 2021

On a Utilitarian Approach to Privacy Preserving Text Generation.

Zekun Xu, Abhinav Aggarwal, Oluwaseyi Feyisetan, Nathanael Teissier

CoRR, 2021

Label Inference Attacks from Log-loss Scores.

Abhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier

Proceedings of the 38th International Conference on Machine Learning, 2021

Density-Aware Differentially Private Textual Perturbations Using Truncated Gumbel Noise.

Nan Xu, Oluwaseyi Feyisetan, Abhinav Aggarwal, Zekun Xu, Nathanael Teissier

Proceedings of the Thirty-Fourth International Florida Artificial Intelligence Research Society Conference, 2021

Research Challenges in Designing Differentially Private Text Generation Mechanisms.

Oluwaseyi Feyisetan, Abhinav Aggarwal, Zekun Xu, Nathanael Teissier

Proceedings of the Thirty-Fourth International Florida Artificial Intelligence Research Society Conference, 2021

2020

A Differentially Private Text Perturbation Method Using a Regularized Mahalanobis Metric.

Zekun Xu, Abhinav Aggarwal, Oluwaseyi Feyisetan, Nathanael Teissier

CoRR, 2020

Differentially Private Adversarial Robustness Through Randomized Perturbations.

Nan Xu, Oluwaseyi Feyisetan, Abhinav Aggarwal, Zekun Xu, Nathanael Teissier

CoRR, 2020

On Primes, Log-Loss Scores and (No) Privacy.

Abhinav Aggarwal, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier

CoRR, 2020

Workshop on Privacy in NLP (PrivateNLP 2020).

Oluwaseyi Feyisetan, Sepideh Ghanavati, Patricia Thaine

Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Hyperbolic Embeddings for Preserving Privacy and Utility in Text.

Oluwaseyi Feyisetan, Tom Diethe, Thomas Drake

Proceedings of the PrivateNLP 2020: Workshop on Privacy in Natural Language Processing, 2020

Calibrating Mechanisms for Privacy Preserving Text Analysis.

Oluwaseyi Feyisetan, Borja Balle, Tom Diethe, Thomas Drake

Proceedings of the PrivateNLP 2020: Workshop on Privacy in Natural Language Processing, 2020

Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations.

Oluwaseyi Feyisetan, Borja Balle, Thomas Drake, Tom Diethe

Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Privacy-Preserving Textual Analysis via Calibrated Perturbations.

Oluwaseyi Feyisetan, Borja Balle

Proceedings of the PrivateNLP 2020: Workshop on Privacy in Natural Language Processing, 2020

Preserving Privacy in Analyses of Textual Data.

Tom Diethe, Oluwaseyi Feyisetan

Proceedings of the PrivateNLP 2020: Workshop on Privacy in Natural Language Processing, 2020

2019

Beyond Monetary Incentives: Experiments in Paid Microtask Contests.

Oluwaseyi Feyisetan, Elena Simperl

ACM Trans. Soc. Comput., 2019

Privacy-preserving Active Learning on Sensitive Data for User Intent Classification.

Oluwaseyi Feyisetan, Thomas Drake, Borja Balle, Tom Diethe

CoRR, 2019

Beyond monetary incentives: experiments in paid microtask contests modelled as continuous-time markov chains.

Oluwaseyi Feyisetan, Elena Simperl

CoRR, 2019

Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text.

Oluwaseyi Feyisetan, Tom Diethe, Thomas Drake

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

2018

An extended study of content and crowdsourcing-related performance factors in named entity annotation.

Oluwaseyi Feyisetan, Elena Simperl, Markus Luczak-Rösch, Ramine Tinati, Nigel Shadbolt

Semantic Web, 2018

2017

Social Incentives in Paid Collaborative Crowdsourcing.

Oluwaseyi Feyisetan, Elena Simperl

ACM Trans. Intell. Syst. Technol., 2017

2016

Please Stay vs Let's Play: Social Pressure Incentives in Paid Collaborative Crowdsourcing.

Oluwaseyi Feyisetan, Elena Simperl

Proceedings of the Web Engineering - 16th International Conference, 2016

2015

Improving Paid Microtasks through Gamification and Adaptive Furtherance Incentives.

Oluwaseyi Feyisetan, Elena Simperl, Max Van Kleek, Nigel Shadbolt

Proceedings of the 24th International Conference on World Wide Web, 2015

Towards Hybrid NER: A Study of Content and Crowdsourcing-Related Performance Factors.

Oluwaseyi Feyisetan, Markus Luczak-Rösch, Elena Simperl, Ramine Tinati, Nigel Shadbolt

Proceedings of the Semantic Web. Latest Advances and New Domains, 2015

2014

Quick-and-clean extraction of linked data entities from microblogs.

Oluwaseyi Feyisetan, Elena Simperl, Ramine Tinati, Markus Luczak-Rösch, Nigel Shadbolt

Proceedings of the 10th International Conference on Semantic Systems, 2014