Related papers: Secure Linear Programming Using Privacy-Preserving…

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The rapid advancement of large language models (LLMs) has revolutionized natural language processing, enabling applications in diverse domains such as healthcare, finance and education. However, the growing reliance on extensive data for…

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Convex programming with linear constraints plays an important role in the operation of a number of everyday systems. However, absent any additional protections, revealing or acting on the solutions to such problems may reveal information…

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This paper has been withdrawn by the author, due to the insecurity against attacks received in quant-ph/0605027v5.

With the increasing demands for privacy protection, privacy-preserving machine learning has been drawing much attention in both academia and industry. However, most existing methods have their limitations in practical applications. On the…

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This paper has been withdrawn by the author

This paper has been withdrawn by the author due to a serious mistake on Lemma 2.4.

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This paper has been withdrawn by the author due a crucial error.

This paper has been withdrawn by the author due to a crucial error in the submission action.