Zobrazeno 1 - 10
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pro vyhledávání: '"Kutzkov, Konstantin"'
Autor:
Kutzkov, Konstantin
Local graph neighborhood sampling is a fundamental computational problem that is at the heart of algorithms for node representation learning. Several works have presented algorithms for learning discrete node embeddings where graph nodes are represen
Externí odkaz:
http://arxiv.org/abs/2211.15114
Autor:
Kutzkov, Konstantin
Representation learning for graphs enables the application of standard machine learning algorithms and data analysis tools to graph data. Replacing discrete unordered objects such as graph nodes by real-valued vectors is at the heart of many approach
Externí odkaz:
http://arxiv.org/abs/2102.04770
Correlation clustering is arguably the most natural formulation of clustering. Given n objects and a pairwise similarity measure, the goal is to cluster the objects so that, to the best possible extent, similar objects are put in the same cluster and
Externí odkaz:
http://arxiv.org/abs/2002.11557
We present novel graph kernels for graphs with node and edge labels that have ordered neighborhoods, i.e. when neighbor nodes follow an order. Graphs with ordered neighborhoods are a natural data representation for evolving graphs where edges are cre
Externí odkaz:
http://arxiv.org/abs/1805.10014
Numerous important problems can be framed as learning from graph data. We propose a framework for learning convolutional neural networks for arbitrary graphs. These graphs may be undirected, directed, and with both discrete and continuous node and ed
Externí odkaz:
http://arxiv.org/abs/1605.05273
Estimating the number of triangles in graph streams using a limited amount of memory has become a popular topic in the last decade. Different variations of the problem have been studied, depending on whether the graph edges are provided in an arbitra
Externí odkaz:
http://arxiv.org/abs/1404.4696
Autor:
Kutzkov, Konstantin, Pagh, Rasmus
Consistent sampling is a technique for specifying, in small space, a subset $S$ of a potentially large universe $U$ such that the elements in $S$ satisfy a suitably chosen sampling condition. Given a subset $\mathcal{I}\subseteq U$ it should be possi
Externí odkaz:
http://arxiv.org/abs/1404.4693
Autor:
Tzougas, George1 (AUTHOR) george.tzougas@hw.ac.uk, Kutzkov, Konstantin2 (AUTHOR)
Publikováno v:
Algorithms. Feb2023, Vol. 16 Issue 2, p99. 28p.
Correlation clustering is perhaps the most natural formulation of clustering. Given $n$ objects and a pairwise similarity measure, the goal is to cluster the objects so that, to the best possible extent, similar objects are put in the same cluster an
Externí odkaz:
http://arxiv.org/abs/1312.5105
We consider the problem of sparse matrix multiplication by the column row method in a distributed setting where the matrix product is not necessarily sparse. We present a surprisingly simple method for "consistent" parallel processing of sparse outer
Externí odkaz:
http://arxiv.org/abs/1210.0461