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Heterogeneous information network3/10/2024 Although existing representation learning methods for heterogeneous information networks do offer performance improvements, they also suffer from several major limitations. ![]() Network representation learning (NRL) is one means for representing network data in low-dimensional space, which has received wide application in the analysis of heterogeneous information networks. If interested, you can download and read the original here. In this article, we're going to take a deep dive into the topics covered in this paper. KDD is the world's top conference for discovering knowledge and mining data. ![]() Not too long ago, the paper "Adversarial Learning on Heterogeneous Information Networks" by Hu Binbin, an algorithm engineer with Ant Financial, was selected by the Knowledge Discovery and Data Mining (KDD) 2019 conference. Get unbeatable offers with up to 90% off on cloud servers and up to $300 rebate for all products! Click here to learn more.
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