Practical Adversarial Robustness in Deep Learning: Problems and Solutions
- Pin-Yu Chen
- Sayak Paul
- 2021
- CVPR 2021
Publications
This is our catalog of publications authored by IBM researchers, in collaboration with the global research community. 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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683 results for Trustworthy AI
Optimization problems for machine learning: A survey
- Claudio Gambella
- Bissan Ghaddar
- et al.
- 2021
- EJOR
A framework for fostering transparency in shared artificial intelligence models by increasing visibility of contributions
- Iain Barclay
- Harrison Taylor
- et al.
- 2020
- Concurrency Computation
A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning: Principals, Recent Advances, and Applications
- Sijia Liu
- Pin-Yu Chen
- et al.
- 2020
- IEEE SPM
Rapid Trust Calibration through Interpretable and Uncertainty-Aware AI
- Richard Tomsett
- Alun Preece
- et al.
- 2020
- Patterns
Towards a GDPR compliant way to secure European cross border Healthcare Industry 4.0
- Xabier Larrucea
- Micha Moffie
- et al.
- 2020
- Computer Standards and Interfaces
The bounded laplace mechanism in differential privacy
- Naoise Holohan
- Spiros Antonatos
- et al.
- 2020
- JPC
Adversarial Robustness Toolbox v1.0.0
- Maria-irina Nicolae
- Mathieu Sinn
- et al.
- 2019
- arXiv
RAPA-convNets: Modified convolutional networks for accelerated training on architectures with analog arrays
- Malte J. Rasch
- Tayfun Gokmen
- et al.
- 2019
- Frontiers in Neuroscience
A blockchain proxy for lightweight iot devices
- 2019
- CVCBT 2019