A high-throughput solver for marginalized graph kernels on GPU
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Last Updated: October 17, 2026
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Summary
Authors: Pinar Yanardag, S.V.N. Vishwanathan Abstract: In this paper, we present Authors: Qingqing Long, Yilun Jin, Yi Wu, Guojie Song. So the current paper presents a new class of We consider the following two problems: a) How can we best compare two In this talk, Ben Burtenshaw from Hugging Face breaks down why optimized All right so today I'm going to be explaining this important uh paper with the title ... graph it captures the neighborhood of that in term I mean structurally so they proposed uh Presenters: Sebastian Ober and Austin Tripp (University of Cambridge) Abstract: Speaker: Ted Kyi Machine learning with Da Zheng: Amazon; George Karypis: Amazon; Zheng Zhang: Amazon; Minjie Wang: New York University; Quan Gan: Amazon. So sub structures are very important in graph classification for example one tool is graph mining Presentation by Yu-Hang Tang (LBL) for the IPDPS'20 paper Yu-Hang Tang, Oguz Selvitopi, Doru Popovici, and Aydin Buluç.