INO-SGD down-weights data in each batch to improve model performance on strongly private data while satisfying individualized differential privacy constraints.
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UNVERDICTED 2representative citing papers
Aligning noisy hidden states in diffusion transformers to clean features from pretrained visual encoders speeds up training over 17x and reaches FID 1.42.
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INO-SGD: Addressing Utility Imbalance under Individualized Differential Privacy
INO-SGD down-weights data in each batch to improve model performance on strongly private data while satisfying individualized differential privacy constraints.
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Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think
Aligning noisy hidden states in diffusion transformers to clean features from pretrained visual encoders speeds up training over 17x and reaches FID 1.42.