# Asymptotics of $\ell_2$ Regularized Network Embeddings

@inproceedings{Davison2022AsymptoticsO, title={Asymptotics of \$\ell\_2\$ Regularized Network Embeddings}, author={Andrew Davison}, year={2022} }

A common approach to solving prediction tasks on large networks, such as node classiﬁcation or link prediction, begin by learning a Euclidean embedding of the nodes of the network, from which traditional machine learning methods can then be applied. This includes methods such as DeepWalk and node2vec, which learn embeddings by optimizing stochastic losses formed over subsamples of the graph at each iteration of stochastic gradient descent. In this paper, we study the effects of adding an (cid…

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