Abstract: Federated learning (FL) is an innovative privacy-preserving machine learning paradigm that enables clients to train a global model without sharing their local data. However, the coexistence ...
With such increased predictive knowledge of solar systems, these anomaly detectors can significantly reduce costs of O&M, a major component of project economics in solar development. There is great ...
The digital landscape is evolving at an unprecedented pace. From smartphones and wearables to autonomous vehicles and hyperscale data centers, the demand for faster, smarter, and more efficient ...
Abstract: Heterogeneous domain adaptation (HDA) aims to address the transfer learning problems where the source domain and target domain are represented by heterogeneous features. The existing HDA ...
When a government imposes tariffs, the stated intention is simple: protect domestic industry, support local jobs, and strengthen national economic resilience. Yet, from the perspective of Austrian ...
Download PDF More Formats on IMF eLibrary Order a Print Copy Create Citation This paper empirically investigates the relationship between uncertainty and trade. We use a gravity model for 143 ...
Using state-of-the-art single-nucleus RNA sequencing, Yao et al. investigate the transcriptomic features of neural stem cells (NSCs) in the human hippocampus to address how they vary across different ...
Designing and manufacturing interconnects is becoming more complex, and more critical to device reliability, as the chip industry shifts from monolithic planar dies to collections of chips and ...
A landmark study sheds new light on the heterogeneity of type 2 diabetes. The researchers employed an innovative algorithm to stratify people with type 2 diabetes using routine data and thus visualize ...
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