Comparado a brute-force (3M vetores), o IVF escaneia apenas ~29K vetores por query (5 clusters × ~5.8K média), uma redução de ~100x. Os 14 dimensões de cada vetor são normalizados para [0, 1] e ...
Abstract: Graph neural networks (GNNs) are powerful models for processing graph data and have demonstrated state-of-the-art performance on many downstream tasks. However, existing GNNs can generally ...
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Abstract: Multi-party computation (MPC) has gained increasing attention in both research and industry, with many protocols adopting the preprocessing model to optimize online performance through the ...
In this work, we have investigated the effect of EEG data preprocessing on the performance of deep learning models. In particular, we have evaluated whether or not raw data can be effectively fed to ...