Abstract: Split learning (SL) aims to protect user data privacy by distributing deep models between the client-server and keeping private data locally. In SL training with multiple clients, the local ...
Abstract: Parallel Split Learning (SL) allows resource-constrained devices that cannot participate in Federated Learning (FL) to train deep neural networks (NNs) by splitting the NN model into parts.
Excitement surrounding stock splits remains a key driver of investor optimism on Wall Street. The most logical candidate to be the blockbuster stock split of the year is a unique member of the ...
A modest $1,000 stake in 3M two decades ago has turned into a surprisingly instructive case study in how dividends and stock splits shape long term returns. By tracing how many shares that money would ...
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