Quick-and-clean extraction of linked data entities from microblogs. - Oluwaseyi Feyisetan; Elena Simperl; Ramine Tinati; Markus Luczak-Rösch; Nigel Shadbolt (SEMANTiCS, 2014)

Towards Hybrid NER: A Study of Content and Crowdsourcing-Related Performance Factors. - Oluwaseyi Feyisetan; Markus Luczak-Rösch; Elena Simperl; Ramine Tinati; Nigel Shadbolt (ESWC, 2015)

Improving Paid Microtasks through Gamification and Adaptive Furtherance Incentives. - Oluwaseyi Feyisetan; Elena Simperl; Max Van Kleek; Nigel Shadbolt (WWW, 2015)

Please Stay vs Let's Play: Social Pressure Incentives in Paid Collaborative Crowdsourcing. - Oluwaseyi Feyisetan; Elena Simperl (ICWE, 2016)

Social Incentives in Paid Collaborative Crowdsourcing. - Oluwaseyi Feyisetan; Elena Simperl (ACM Trans. Intell. Syst. Technol., 2017)

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)

Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text. - Oluwaseyi Feyisetan; Tom Diethe; Thomas Drake (ICDM, 2019)

Beyond monetary incentives: experiments in paid microtask contests modelled as continuous-time markov chains. - Oluwaseyi Feyisetan; Elena Simperl (CoRR, 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. - Oluwaseyi Feyisetan; Elena Simperl (ACM Trans. Soc. Comput., 2019)

Preserving Privacy in Analyses of Textual Data. - Tom Diethe; Oluwaseyi Feyisetan (PrivateNLP@WSDM, 2020)

Privacy-Preserving Textual Analysis via Calibrated Perturbations. - Oluwaseyi Feyisetan; Borja Balle (PrivateNLP@WSDM, 2020)

Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations. - Oluwaseyi Feyisetan; Borja Balle; Thomas Drake; Tom Diethe (WSDM, 2020)

Calibrating Mechanisms for Privacy Preserving Text Analysis. - Oluwaseyi Feyisetan; Borja Balle; Tom Diethe; Thomas Drake (PrivateNLP@WSDM, 2020)

Hyperbolic Embeddings for Preserving Privacy and Utility in Text. - Oluwaseyi Feyisetan; Tom Diethe; Thomas Drake (PrivateNLP@WSDM, 2020)

Workshop on Privacy in NLP (PrivateNLP 2020). - Oluwaseyi Feyisetan; Sepideh Ghanavati; Patricia Thaine (WSDM, 2020)

On Primes, Log-Loss Scores and (No) Privacy. - Abhinav Aggarwal; Zekun Xu; 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)

A Differentially Private Text Perturbation Method Using a Regularized Mahalanobis Metric. - Zekun Xu; Abhinav Aggarwal; Oluwaseyi Feyisetan; Nathanael Teissier (CoRR, 2020)

Research Challenges in Designing Differentially Private Text Generation Mechanisms. - Oluwaseyi Feyisetan; Abhinav Aggarwal; Zekun Xu; Nathanael Teissier (FLAIRS, 2021)

Density-Aware Differentially Private Textual Perturbations Using Truncated Gumbel Noise. - Nan Xu; Oluwaseyi Feyisetan; Abhinav Aggarwal; Zekun Xu; Nathanael Teissier (FLAIRS, 2021)

Label Inference Attacks from Log-loss Scores. - Abhinav Aggarwal; Shiva Prasad Kasiviswanathan; Zekun Xu; Oluwaseyi Feyisetan; Nathanael Teissier (ICML, 2021)

On a Utilitarian Approach to Privacy Preserving Text Generation. - Zekun Xu; Abhinav Aggarwal; Oluwaseyi Feyisetan; Nathanael Teissier (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)

BRR: Preserving Privacy of Text Data Efficiently on Device. - Ricardo Silva Carvalho; Theodore Vasiloudis; Oluwaseyi Feyisetan (CoRR, 2021)

TEM: High Utility Metric Differential Privacy on Text. - Ricardo Silva Carvalho; Theodore Vasiloudis; Oluwaseyi Feyisetan (CoRR, 2021)

Reconstructing Test Labels from Noisy Loss Functions. - Abhinav Aggarwal; Shiva Prasad Kasiviswanathan; Zekun Xu; Oluwaseyi Feyisetan; Nathanael Teissier (AISTATS, 2022)

TEM: High Utility Metric Differential Privacy on Text. - Ricardo Silva Carvalho; Theodore Vasiloudis; Oluwaseyi Feyisetan; Ke Wang 001 (SDM, 2023)

Fast Training Dataset Attribution via In-Context Learning. - Milad Fotouhi; Mohammad Taha Bahadori; Oluwaseyi Feyisetan; Payman Arabshahi; David Heckerman (CoRR, 2024)

Removing Spurious Correlation from Neural Network Interpretations. - Milad Fotouhi; Mohammad Taha Bahadori; Oluwaseyi Feyisetan; Payman Arabshahi; David Heckerman (CoRR, 2024)