Abstract: In distributed learning systems, ensuring efficient communication and privacy protection are two significant challenges. Although several existing works have attempted to address these ...
Recent years have witnessed the unprecedented development of Industry 4.0 and the Industrial Internet of Things. These two ...
A new paradigm in automated quantitative analysis designed to optimize market execution and risk synchronization for ...
A People Analytics study of 205 tech professionals found that promotions, internal mobility, and career momentum are stronger predictors of early attrition than workplace culture.
Personalized algorithms may quietly sabotage how people learn, nudging them into narrow tunnels of information even when they start with zero prior knowledge. In the study, participants using ...
The financial industry's embrace of machine learning has reached a tipping point in 2026, moving from experimental adoption to a core operational necessity fraught with regulatory peril. Recent joint ...
A new study published in Frontiers in Computer Science introduces a decentralized cybersecurity model that combines federated ...
Machine learning's transformative shift mirrors the MapReduce moment, revolutionizing efficiency with decentralized consensus algorithms.
Abstract: Distributed path planning for multiple unmanned aerial vehicles (UAVs) plays a significant role in data collection systems. However, insufficient collaboration among multiple UAVs and ...
Unmanned surface vehicles (USVs) nowadays have been widely used in ocean observation missions, helping researchers to monitor climate change, collect environmental data, and observe marine ecosystem ...
The recent emergence of DeepSeek’s remarkably cost-efficient large language models has sent shockwaves through the AI industry, not just for what it achieved, but for how efficiently it achieved it.
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