Tomáš Nováček presents node2vec: Scalable feature learning for networks

On 2020-04-14 11:00:00
This reading group will be organized as video conference (Instructions will
appear in soon)

Reading group on the work "node2vec: Scalable feature learning for networks",
A. Grover, J. Leskovec. ACM SIGKDD 2016. Presented by Tomáš Nováček

Paper abstract: Prediction tasks over nodes and edges in networks require
careful effort in engineering features used by learning algorithms. Recent
research in the broader field of representation learning has led to significant
progress in automating prediction by learning the features themselves. However,
present feature learning approaches are not expressive enough to capture the
diversity of connectivity patterns observed in networks. Here we propose
node2vec, an algorithmic framework for learning continuous feature
representations for nodes in networks. In node2vec, we learn a mapping of nodes
to a low-dimensional space of features that maximizes the likelihood of
preserving network neighborhoods of nodes. We define a flexible notion of a
node's network neighborhood and design a biased random walk procedure, which
efficiently explores diverse neighborhoods. Our algorithm generalizes prior
work which is based on rigid notions of network neighborhoods, and we argue
that the added flexibility in exploring neighborhoods is the key to learning
richer representations. We demonstrate the efficacy of node2vec over existing
state-of-the-art techniques on multi-label classification and link prediction
in several real-world networks from diverse domains. Taken together, our work
represents a new way for efficiently learning state-of-the-art task-independent
representations in complex networks.

Paper URL:

Instructions for participants: The reading group studies the literature in the
field of pattern recognition and computer vision. At each meeting one or more
papers are prepared for presentation by a single person, the presenter. The
meetings are open to anyone, disregarding their background. It is assumed that
everyone attending the reading group has, at least briefly, read the paper –
not necessarily understanding everything. Attendants should preferably send
questions about the unclear parts to the speaker at least one day in advance.
During the presentation we aim to have a fruitful discussion, a critical
analysis of the paper, as well as brainstorming for creative extensions.

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Responsible person: Petr Pošík