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Random Search as a Baseline for Sparse Neural Network Architecture Search
We apply Random Search on the node space of an overparameterized network with the goal of finding better initialized sparse sub-networks that are positioned more advantageously in the loss landscape.
Synthetic Query Generation for Privacy-Preserving Deep Retrieval Systems using Differentially Private Language Models
We address the challenge of ensuring differential privacy (DP) guarantees in training deep retrieval systems.
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