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Breaking 3-Factor Approximation for Correlation Clustering in Polylogarithmic Rounds
Our approach is inspired by Awerbuch, Khandekar, and Rao's [AKR12] length-constrained multi-commodity flow algorithm, where we develop an efficient parallel algorithm to solve a truncated correlation clustering linear program of Charikar, Guruswami, and Wirth [CGW05].
Self-supervised Representation Learning on Electronic Health Records with Graph Kernel Infomax
We propose Graph Kernel Infomax, a self-supervised graph kernel learning approach on the graphical representation of EHR, to overcome the previous problems.
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