Towards an Accountable and Reproducible Federated Learning: A FactSheets Approach
- Nathalie Baracaldo Angel
- Ali Anwar
- et al.
- 2022
- arXiv
Paper
Publications
58 results for Nathalie Baracaldo
Machine Learning Security and Privacy
- Nathalie Baracaldo
- Alina Oprea
- 2021
- IEEE Security and Privacy
PaperFLoRA: Single-shot Hyper-parameter Optimization for Federated Learning
- Yi Zhou
- Parikshit Ram
- et al.
- 2021
- NeurIPS 2021
Workshop paperFedV: Privacy-Preserving Federated Learning over Vertically Partitioned Data
- Runhua Xu
- Nathalie Baracaldo
- et al.
- 2021
- AISec/CCS 2021
Conference paperAccountable Federated Machine Learning in Government: Engineering and Management Insights
- Dian Balta
- Mahdi Sellami
- et al.
- 2021
- ePart 2021
Conference paperLEGATO: A LayerwisE Gradient AggregaTiOn Algorithm for Mitigating Byzantine Attacks in Federated Learning
- Kamala Varma
- Yi Zhou
- et al.
- 2021
- CLOUD 2021
Conference paperTIFF: Tokenized Incentive for Federated Learning
- Jingoo Han
- Ahmad Faraz Khan
- et al.
- 2022
- CLOUD 2022
Conference paperDeTrust-FL: Privacy-Preserving Federated Learning in Decentralized Trust Setting
- Runhua Xu
- Nathalie Baracaldo
- et al.
- 2022
- CLOUD 2022
Conference paperThe Design and Development of a Game to Study Backdoor Poisoning Attacks: The Backdoor Game
- Zahra Ashktorab
- Casey Dugan
- et al.
- 2021
- IUI 2021
Conference paperCurse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning
- Syed Zawad
- Ahsan Ali
- et al.
- 2021
- AAAI 2021
Conference paper