Nidham
Gazagnadou
Publications
The interest in federated learning has surged in recent research due to its unique ability to train a global model using privacy-secured information held locally on each client. This paper pays particular attention to the issue of client-side model heterogeneity, a pervasive…
Hand-crafted image quality metrics, such as PSNR and SSIM, are commonly used to evaluate model privacy risk under reconstruction attacks. Under these metrics, reconstructed images that are determined to resemble the original one generally indicate more privacy leakage. Image…
Blog
December 13, 2023 | Events
Sony AI Reveals New Research Contributions at NeurIPS 2023
Sony Group Corporation and Sony AI have been active participants in the annual NeurIPS Conference for years, contributing pivotal research that has helped to propel the fields of artificial intelligence and machine learning forwar…
Sony Group Corporation and Sony AI have been active participants in the annual NeurIPS Conference for years, contributing pivotal …
August 7, 2023 | Machine Learning
Privacy-Preserving Machine Learning Blog Series: Practicing Privacy by Design
Privacy-Preserving Machine Learning Blog SeriesAt Sony AI, the Privacy-Preserving Machine Learning (PPML) team focuses on fundamental and applied research in computer vision privacy. Their innovative research aims to apply these n…
Privacy-Preserving Machine Learning Blog SeriesAt Sony AI, the Privacy-Preserving Machine Learning (PPML) team focuses on fundamen…
July 13, 2023 | Life at Sony AI
Meet the Team #8: Weiming Zhuang, Nidham Gazagnadou, Chen Chen
At Sony AI, the Privacy-Preserving Machine Learning (PPML) team focuses on fundamental and applied research in computer vision privacy. Their innovative research aims to apply these novel ideas to real-world AI applications. In th…
At Sony AI, the Privacy-Preserving Machine Learning (PPML) team focuses on fundamental and applied research in computer vision pri…
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