Publications

This is our catalog of recent publications authored by IBM researchers, in collaboration with the global research community. We’re currently adding our back catalog of more than 110,000 publications. It’s an ever-growing body of work that shows why IBM is one of the most important contributors to modern computing.

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Year

15 results for AI Privacy

Differentially Private Stochastic Coordinate Descent
- - Georgios Damaskinos
  - Celestine Mendler-Dünner
  - et al.
- 2021
- AAAI 2021
The Discrete Gaussian for Differential Privacy
- - Clément L. Canonne
  - Gautam Kamath
  - et al.
- 2020
- NeurIPS 2020
New oracle-efficient algorithms for private synthetic data release
- - Giuseppe Vietri
  - Grace Tian
  - et al.
- 2020
- ICML 2020
IBM Federated Learning Community Edition: An Interactive Demonstration
- - Laura Wynter
- 2020
- NeurIPS 2020
Addressing Unique Fairness Obstacles within Federated Learning
- - Annie Abay
  - Ebube Chuba
  - et al.
- 2021
- AAAI 2021
FAT: Federated Adversarial Training
- - Giulio Zizzo
  - Ambrish Rawat
  - et al.
- 2020
- NeurIPS 2020
Explainable Link Prediction for Privacy-Preserving Contact Tracing
- - Balaji Ganesan
  - Hima Patel
  - et al.
- 2020
- NeurIPS 2020
Learning to Design Fair and Private Voting Rules
- - Farhad Mohsin
  - Ao Liu
  - et al.
- 2020
- NeurIPS 2020
NN-EMD: Efficiently Training Neural Networks Using Encrypted Multi-Sourced Datasets
- - Runhua Xu
  - James Joshi
  - et al.
- 2021
- IEEE TDSC
How to Democratise and Protect AI: Fair and Differentially Private Decentralised Deep Learning
- - Lingjuan Lyu
  - Yitong Li
  - et al.
- 2020
- IEEE TDSC