Search Results for author: Ming-Chang Yang

Found 3 papers, 1 papers with code

Understanding and Improving Proximity Graph based Maximum Inner Product Search

no code implementations30 Sep 2019 Jie Liu, Xiao Yan, Xinyan Dai, Zhirong Li, James Cheng, Ming-Chang Yang

Then we explain the good performance of ip-NSW as matching the norm bias of the MIPS problem - large norm items have big in-degrees in the ip-NSW proximity graph and a walk on the graph spends the majority of computation on these items, thus effectively avoids unnecessary computation on small norm items.

A Representation Learning Framework for Property Graphs

no code implementations Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining 2019 Yifan Hou, Hongzhi Chen, Changji Li, James Cheng, Ming-Chang Yang

Representation learning on graphs, also called graph embedding, has demonstrated its significant impact on a series of machine learning applications such as classification, prediction and recommendation.

Graph Embedding Graph Representation Learning +3

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