Results 31 to 40 of about 2,805,373 (250)
B2-Sampling: Fusing Balanced and Biased Sampling for Graph Contrastive Learning
, 2023 Graph contrastive learning (GCL), aiming for an embedding space where semantically similar nodes are closer, has been widely applied in graph-structured data.
Liu, J +5 more
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SORAG: Synthetic Data Over-Sampling Strategy on Multi-Label Graphs
Remote Sensing, 2022 In many real-world networks of interest in the field of remote sensing (e.g., public transport networks), nodes are associated with multiple labels, and node classes are imbalanced; that is, some classes have significantly fewer samples than others ...
Yijun Duan +6 more
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Evaluation of respondent-driven sampling [PDF]
, 2012 Respondent-driven sampling produced a generally representative sample of this well-connected nonhidden population. However, current respondent-driven sampling inference methods failed to reduce bias when it occurred.
Joseph Katongole +34 more
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Mosar: Efficiently Characterizing Both Frequent and Rare Motifs in Large Graphs
Applied Sciences, 2022 Due to high computational costs, exploring motif statistics (such as motif frequencies) of a large graph can be challenging. This is useful for understanding complex networks such as social and biological networks. To address this challenge, many methods
Wenhua Guo +4 more
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On Sampling Colorings of Bipartite Graphs [PDF]
Discrete Mathematics & Theoretical Computer Science, 2006 We study the problem of efficiently sampling k-colorings of bipartite graphs. We show that a class of markov chains cannot be used as efficient samplers. Precisely, we show that, for any k, 6 ≤ k ≤ n^\1/3-ε \, ε > 0 fixed, \emphalmost every bipartite graph on n+n vertices is such that the mixing time of any markov chain asymptotically uniform on its
R. Balasubramanian, C. R. Subramanian
openaire +5 more sources
, 2011 In this paper, we introduce ideal graph of a graph and study some of its properties. We characterize connectedness, isomorphism of graphs and coloring property of a graph using ideal graph.
Manoharan, R., Vasuki, R.
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Graph Sampling for Covariance Estimation [PDF]
IEEE Transactions on Signal and Information Processing over Networks, 2017 In this paper the focus is on subsampling as well as reconstructing the second-order statistics of signals residing on nodes of arbitrary undirected graphs. Second-order stationary graph signals may be obtained by graph filtering zero-mean white noise and they admit a well-defined power spectrum whose shape is determined by the frequency response of ...
Sundeep Prabhakar Chepuri, Geert Leus
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Accelerating graph sampling for graph machine learning using GPUs [PDF]
Proceedings of the Sixteenth European Conference on Computer Systems, 2021 Published in EuroSys ...
Abhinav Jangda +3 more
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Towards a Maude tool for model checking temporal graph properties [PDF]
, 2011 We present our prototypical tool for the verification of graph transformation systems. The major novelty of our tool is that it provides a model checker for temporal graph properties based on counterpart semantics for quantified m-calculi.
Lluch-Lafuente, Alberto +4 more
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Negative Sampling Method for Fusing Knowledge Graph [PDF]
Jisuanji kexueIn order to solve the problem of information overload,recommender systems have been widely studied.Since it is difficult to obtain a large amount of high-quality explicit feedback data,implicit feedback data becomes the mainstream choice for training re ...
LU Haiyang, LIU Xianhui, HOU Wenlong
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