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Image Classification with Differential Privacy
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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Image Classification with Differential Privacy is an improved version of the image classification task whereby the final classification output only describe the patterns of groups within the dataset while withholding information about individuals in the dataset.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Private, fair and accurate: Training large-scale, privacy-preserving AI models in medical imaging
Equivariant Differentially Private Deep Learning: Why DP-SGD Needs Sparser Models
TAN Without a Burn: Scaling Laws of DP-SGD
SmoothNets: Optimizing CNN architecture design for differentially private deep learning
Unlocking High-Accuracy Differentially Private Image Classification through Scale
Toward Training at ImageNet Scale with Differential Privacy
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