Abstract: The performance of distributed applications has long been hindered by network communication, which has emerged as a significant bottleneck. At the core of this issue, the many-to-one incast ...
Abstract: Incomplete or outdated inventories of railway infrastructures may disrupt the railway sector’s administration and maintenance of transportation infrastructure, thus posing potential threats ...
Abstract: Utilizing messages from teammates can improve coordination in cooperative multiagent reinforcement learning (MARL). Previous works typically combine raw messages of teammates with local ...
Abstract: The unstructured, unordered and inherent irregular sampling properties presents difficulties for accurate and efficient realizing semantic segmentation of large-scale 3D point cloud. The ...
AUBURN AND WINDHAM , NH, UNITED STATES, March 16, 2026 /EINPresswire.com/ — The Town of Windham, NH and Freedom Energy Logistics (Freedom Energy) announced that ...
Abstract: Accurately mappingtree stems is essentialfor the analysis and estimation of tree parameters derived from terrestrial laser scanning (TLS) point clouds, including critical measurements such ...
The aggregation pipeline is a powerful tool that allows developers to perform advanced data analysis and manipulation on their collections. The pipeline is a sequence of data processing operations, ...
Abstract: Federated learning (FL), as a promising machine learning paradigm for large-scale distributed data, faces two security challenges of privacy and robustness: the transmitted model updates ...
Abstract: Change Point Detection (CPD) aims to identify moments of abrupt distribution shifts in data streams. Real-world high-dimensional CPD remains challenging due to data pattern complexity and ...
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 ...