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The Limits and Potentials of Local SGD for Distributed Heterogeneous Learning with Intermittent Communication
In this paper, we provide new lower bounds for local SGD under existing first-order data heterogeneity assumptions, showing that these assumptions are insufficient to prove the effectiveness of local update steps.
Noisy Interpolation Learning with Shallow Univariate ReLU Networks
We show overfitting is tempered (with high probability) when measured with respect to the $L_1$ loss, but also show that the situation is more complex than suggested by Mallinar et.
Community Detection in the Hypergraph SBM: Exact Recovery Given the Similarity Matrix
In this paper, we consider community detection in hypergraphs drawn from the $hypergraph$ $stochastic$ $block$ $model$ (HSBM), with a focus on exact community recovery.
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