Abstract: Secure aggregation becomes a major solution to providing privacy for federated learning. Secure aggregation for mobile devices typically relies on Shamir secret sharing (SSS) to achieve ...
Abstract: In this paper, we propose an Aggregation and Separation Domain Generalization (ASDG) method for Audio DeepFake Detection (ADD). Fake speech generated from different methods exhibits varied ...
Abstract: The performance of Federated Learning (FL) hinges on the effectiveness of utilizing knowledge from distributed datasets. Traditional FL methods adopt an aggregate-then-adapt framework, where ...
Abstract: Transformer has recently gained considerable popularity in low-level vision tasks, including image super-resolution (SR). These networks utilize self-attention along different dimensions, ...
Abstract: Multipoint dynamic aggregation (MPDA) is a multirobot task allocation problem, which requires the collaborative scheduling of multiple robots to complete time-varying tasks distributed on a ...
Abstract: Existing methods for learning 3D point cloud representation often use a single dataset-specific training and testing approach, leading to performance drops due to significant domain shifts ...
Abstract: Effective sampling plays a critical role in the preprocessing of 3D point cloud data, directly impacting the performance of downstream models. Traditional Farthest Point Sampling (FPS) ...