As vehicle architectures evolve toward centralized and software-defined systems, automotive developers require flexible toolchains that support heterogeneous hardware platforms, modern programming ...

Abstract: The distribution of quantized observations is inherently non-Gaussian and often implicit, rendering conventional Ziv-Zakai bounds (ZZBs) and other global ...

Abstract: Federated learning (FL) has been widely regarded as a promising paradigm for privacy preservation of raw data in machine learning. Although data privacy in FL is locally protected to some ...