Mechanistically-guided materials chemistry: synthesis of new ternary nitrides, CaZrN$_2$ and CaHfN$_2$

Posted by dbos Berkeley

Kavli Affiliate: Kristin A. Persson | First 5 Authors: Christopher L. Rom, Andrew Novick, Matthew J. McDermott, Andrey A. Yakovenko, Jessica R. Gallawa | Summary: Recent computational studies have predicted many new ternary nitrides, revealing synthetic opportunities in this underexplored phase space. However, synthesizing new ternary nitrides is difficult, in part because intermediate and product […]


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Privacy-Preserving Federated Learning over Vertically and Horizontally Partitioned Data for Financial Anomaly Detection

Posted by dbos UCAS

Kavli Affiliate: Yi Zhou | First 5 Authors: Swanand Ravindra Kadhe, Heiko Ludwig, Nathalie Baracaldo, Alan King, Yi Zhou | Summary: The effective detection of evidence of financial anomalies requires collaboration among multiple entities who own a diverse set of data, such as a payment network system (PNS) and its partner banks. Trust among these […]


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Defect two-point functions in 6d (2,0) theories

Posted by dbos UCAS

Kavli Affiliate: Xinan Zhou | First 5 Authors: Junding Chen, Aleix Gimenez-Grau, Xinan Zhou, , | Summary: We consider correlation functions in 6d $(2,0)$ theories of two $frac{1}{2}$-BPS operators inserted away from a $frac{1}{2}$-BPS surface defect. In the large central charge limit the leading connected contribution corresponds to sums of tree-level Witten diagram in AdS$_7times$S$^4$ […]


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Maximum Knowledge Orthogonality Reconstruction with Gradients in Federated Learning

Posted by dbos Berkeley

Kavli Affiliate: Feng Wang | First 5 Authors: Feng Wang, Senem Velipasalar, M. Cenk Gursoy, , | Summary: Federated learning (FL) aims at keeping client data local to preserve privacy. Instead of gathering the data itself, the server only collects aggregated gradient updates from clients. Following the popularity of FL, there has been considerable amount […]


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