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The present invention relates to probabilistic inference based on secure multi-party computation (SMPC) techniques, and more particularly to Confidential Inference and Model Protection. The present invention addresses the privacy concern of model owners and ML client, by using the confidential inference and model protection aka CoInMPro, a technique to boost privacy of model parameters and client input during ML inference without affecting accuracy by paying a marginal performance cost.</text>
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