Pages that link to "Item:Q2691579"
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The following pages link to Maliciously secure matrix multiplication with applications to private deep learning (Q2691579):
Displaying 11 items.
- SPEED: secure, private, and efficient deep learning (Q2051270) (← links)
- Improving the efficiency of AES protocols in multi-party computation (Q2145388) (← links)
- \( \mathsf{Rabbit} \): efficient comparison for secure multi-party computation (Q2145391) (← links)
- Improved threshold signatures, proactive secret sharing, and input certification from LSS isomorphisms (Q2146105) (← links)
- High-precision bootstrapping for approximate homomorphic encryption by error variance minimization (Q2170015) (← links)
- Privacy preserving multi-party computation delegation for deep learning in cloud computing (Q2198099) (← links)
- Privacy-preserving distributed deep learning based on secret sharing (Q2663489) (← links)
- On the Scaled Inverse of $(x^i-x^j)$ modulo Cyclotomic Polynomial of the form $\Phi_{p^s}(x)$ or $\Phi_{p^s q^t}(x)$ (Q5074074) (← links)
- \textsf{Through the looking-glass}: benchmarking secure multi-party computation comparisons for \textsf{ReLU}'s (Q6164395) (← links)
- Multiparty homomorphic machine learning with data security and model preservation (Q6483807) (← links)
- Private Decision Tree Evaluation with Constant Rounds via (Only) Fair SS-4PC (Q6488389) (← links)
