QUOTIENT achieves 50X faster WAN training time and 6% higher absolute accuracy for secure two-party DNN training by jointly optimizing a discretized training algorithm with a tailored secure protocol.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2019 3verdicts
UNVERDICTED 3representative citing papers
signADAM and signADAM++ are new first-order optimizers that incorporate sign operations and a confidence-based sparsity mechanism, with claimed empirical superiority and theoretical convergence over ADAM and sign-based baselines.
MA-DNN augments DNNs with per-user memory vectors capturing likes and dislikes to exploit historical behavior for CTR prediction while remaining simpler than RNNs.
citing papers explorer
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QUOTIENT: Two-Party Secure Neural Network Training and Prediction
QUOTIENT achieves 50X faster WAN training time and 6% higher absolute accuracy for secure two-party DNN training by jointly optimizing a discretized training algorithm with a tailored secure protocol.
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signADAM: Learning Confidences for Deep Neural Networks
signADAM and signADAM++ are new first-order optimizers that incorporate sign operations and a confidence-based sparsity mechanism, with claimed empirical superiority and theoretical convergence over ADAM and sign-based baselines.
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Click-Through Rate Prediction with the User Memory Network
MA-DNN augments DNNs with per-user memory vectors capturing likes and dislikes to exploit historical behavior for CTR prediction while remaining simpler than RNNs.