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Shake to Leak: Fine-tuning Diffusion Models Can Amplify the Generative Privacy Risk., , , и . SaTML, стр. 18-32. IEEE, (2024)Can Pruning Improve Certified Robustness of Neural Networks?, , , , и . Trans. Mach. Learn. Res., (2023)Sparse Cocktail: Every Sparse Pattern Every Sparse Ratio All At Once., , , , , , , , и . ICML, OpenReview.net, (2024)Accelerable Lottery Tickets with the Mixed-Precision Quantization., , , , , , , и . CVPR Workshops, стр. 4604-4612. IEEE, (2023)Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression., , , , , , , , , и 5 other автор(ы). ICML, OpenReview.net, (2024)DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer., , , , , и . ICLR, OpenReview.net, (2024)ARMIN: Towards a More Efficient and Light-weight Recurrent Memory Network., , , , , и . IJCAI, стр. 2944-2951. ijcai.org, (2019)AttPool: Towards Hierarchical Feature Representation in Graph Convolutional Networks via Attention Mechanism., , , , и . ICCV, стр. 6479-6488. IEEE, (2019)Can pruning improve certified robustness of neural networks?, , , , и . CoRR, (2022)Tailored Phase Transformation of CsPbI2Br Films by Copper(II) Bromide for High-Performance All-Inorganic Perovskite Solar Cells. (2019)