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Awesome Machine Learning Interpretability A maintained and curated list of practical and awesome responsible machine learning resources. If you want to contribute to this list (and please do!), read over the contribution guidelines, send a pull request, or file an issue. If something you contribu...
Toward Understanding the Influence of Individual Clients in Federated Learning Shanghai Jiao Tong University;The University of Texas at Dallas video Provably Secure Federated Learning against Malicious Clients Duke University videoslides Personalized Cross-Silo Federated Learning on Non-IID Data Simon Fraser...
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5.2. Machine Learning Prospects for LiDAR Given the rapidly increasing rate and expanding spatial extent of aerial LiDAR acquisition, especially in the form of open-access, national-level scans [84], there is a strong motivation for investigating the use of ML approaches for LiDAR smoothing, as ...
In addition, lesions imaged in Doha were clinically more advanced than those imaged in Dallas. These differences in race, gender, and age between patient populations and in malignancy stage could potentially affect the autofluorescence properties of the imaged oral tissues. Nevertheless, it was ...
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In this video fromSC18in Dallas, Ziv Kalminovich from VMware describes how the company’s powerful virtualization capabilities bringflexibility and performanceto HPC workloads. High Performance Computing workloads are forecasted to be one of the fastest-growing workload types through 2020. With VM...