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ORCIDOluwaseyi Feyisetan
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Journal Articles
- 2019
[j3]Oluwaseyi Feyisetan, Elena Simperl
:
Beyond Monetary Incentives: Experiments in Paid Microtask Contests. ACM Trans. Soc. Comput. 2(2): 6:1-6:31 (2019)- 2018
- [j2]Oluwaseyi Feyisetan, Elena Simperl, Markus Luczak-Rösch, Ramine Tinati, Nigel Shadbolt:
An extended study of content and crowdsourcing-related performance factors in named entity annotation. Semantic Web 9(3): 355-379 (2018) - 2017
- [j1]Oluwaseyi Feyisetan, Elena Simperl:
Social Incentives in Paid Collaborative Crowdsourcing. ACM Trans. Intell. Syst. Technol. 8(6): 73:1-73:31 (2017)
Conference and Workshop Papers
- 2023
- [c16]Ricardo Silva Carvalho, Theodore Vasiloudis, Oluwaseyi Feyisetan, Ke Wang:
TEM: High Utility Metric Differential Privacy on Text. SDM 2023: 883-890 - 2022
- [c15]Abhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier:
Reconstructing Test Labels from Noisy Loss Functions. AISTATS 2022: 8570-8591 - 2021
- [c14]Oluwaseyi Feyisetan, Abhinav Aggarwal, Zekun Xu, Nathanael Teissier:
Research Challenges in Designing Differentially Private Text Generation Mechanisms. FLAIRS 2021 - [c13]Nan Xu, Oluwaseyi Feyisetan, Abhinav Aggarwal, Zekun Xu, Nathanael Teissier:
Density-Aware Differentially Private Textual Perturbations Using Truncated Gumbel Noise. FLAIRS 2021 - [c12]Abhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier:
Label Inference Attacks from Log-loss Scores. ICML 2021: 120-129 - 2020
- [c11]Tom Diethe, Oluwaseyi Feyisetan:
Preserving Privacy in Analyses of Textual Data. PrivateNLP@WSDM 2020: 1-3 - [c10]Oluwaseyi Feyisetan, Borja Balle, Tom Diethe, Thomas Drake:
Calibrating Mechanisms for Privacy Preserving Text Analysis. PrivateNLP@WSDM 2020: 8-11 - [c9]Oluwaseyi Feyisetan, Tom Diethe, Thomas Drake:
Hyperbolic Embeddings for Preserving Privacy and Utility in Text. PrivateNLP@WSDM 2020: 39-40 - [c8]Oluwaseyi Feyisetan, Borja Balle:
Privacy-Preserving Textual Analysis via Calibrated Perturbations. PrivateNLP@WSDM 2020: 41-42 - [c7]Oluwaseyi Feyisetan, Borja Balle, Thomas Drake, Tom Diethe:
Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations. WSDM 2020: 178-186 - [c6]Oluwaseyi Feyisetan, Sepideh Ghanavati, Patricia Thaine:
Workshop on Privacy in NLP (PrivateNLP 2020). WSDM 2020: 903-904 - 2019
- [c5]Oluwaseyi Feyisetan, Tom Diethe, Thomas Drake:
Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text. ICDM 2019: 210-219 - 2016
- [c4]Oluwaseyi Feyisetan, Elena Simperl:
Please Stay vs Let's Play: Social Pressure Incentives in Paid Collaborative Crowdsourcing. ICWE 2016: 405-412 - 2015
- [c3]Oluwaseyi Feyisetan, Markus Luczak-Rösch, Elena Simperl, Ramine Tinati, Nigel Shadbolt:
Towards Hybrid NER: A Study of Content and Crowdsourcing-Related Performance Factors. ESWC 2015: 525-540 - [c2]Oluwaseyi Feyisetan, Elena Simperl, Max Van Kleek, Nigel Shadbolt:
Improving Paid Microtasks through Gamification and Adaptive Furtherance Incentives. WWW 2015: 333-343 - 2014
- [c1]Oluwaseyi Feyisetan, Elena Simperl, Ramine Tinati, Markus Luczak-Rösch, Nigel Shadbolt:
Quick-and-clean extraction of linked data entities from microblogs. SEMANTiCS 2014: 5-12
Editorship
- 2020
- [e1]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]
Informal and Other Publications
- 2024
- [i14]Milad Fotouhi, Mohammad Taha Bahadori, Oluwaseyi Feyisetan, Payman Arabshahi, David Heckerman:
Fast Training Dataset Attribution via In-Context Learning. CoRR abs/2408.11852 (2024) - 2021
- [i13]Zekun Xu, Abhinav Aggarwal, Oluwaseyi Feyisetan, Nathanael Teissier:
On a Utilitarian Approach to Privacy Preserving Text Generation. CoRR abs/2104.11838 (2021) - [i12]Abhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier:
Label Inference Attacks from Log-loss Scores. CoRR abs/2105.08266 (2021) - [i11]Abhinav Aggarwal, Shiva Prasad Kasiviswanathan, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier:
On Codomain Separability and Label Inference from (Noisy) Loss Functions. CoRR abs/2107.03022 (2021) - [i10]Ricardo Silva Carvalho, Theodore Vasiloudis, Oluwaseyi Feyisetan:
BRR: Preserving Privacy of Text Data Efficiently on Device. CoRR abs/2107.07923 (2021) - [i9]Ricardo Silva Carvalho, Theodore Vasiloudis, Oluwaseyi Feyisetan:
TEM: High Utility Metric Differential Privacy on Text. CoRR abs/2107.07928 (2021) - 2020
- [i8]Abhinav Aggarwal, Zekun Xu, Oluwaseyi Feyisetan, Nathanael Teissier:
On Primes, Log-Loss Scores and (No) Privacy. CoRR abs/2009.08559 (2020) - [i7]Nan Xu, Oluwaseyi Feyisetan, Abhinav Aggarwal, Zekun Xu, Nathanael Teissier:
Differentially Private Adversarial Robustness Through Randomized Perturbations. CoRR abs/2009.12718 (2020) - [i6]Zekun Xu, Abhinav Aggarwal, Oluwaseyi Feyisetan, Nathanael Teissier:
A Differentially Private Text Perturbation Method Using a Regularized Mahalanobis Metric. CoRR abs/2010.11947 (2020) - [i5]Oluwaseyi Feyisetan, Abhinav Aggarwal, Zekun Xu, Nathanael Teissier:
Research Challenges in Designing Differentially Private Text Generation Mechanisms. CoRR abs/2012.05403 (2020) - 2019
- [i4]Oluwaseyi Feyisetan, Elena Simperl:
Beyond monetary incentives: experiments in paid microtask contests modelled as continuous-time markov chains. CoRR abs/1901.05670 (2019) - [i3]Oluwaseyi Feyisetan, Thomas Drake, Borja Balle, Tom Diethe:
Privacy-preserving Active Learning on Sensitive Data for User Intent Classification. CoRR abs/1903.11112 (2019) - [i2]Oluwaseyi Feyisetan, Borja Balle, Thomas Drake, Tom Diethe:
Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations. CoRR abs/1910.08902 (2019) - [i1]Oluwaseyi Feyisetan, Tom Diethe, Thomas Drake:
Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text. CoRR abs/1910.08917 (2019)
Coauthor Index
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