6 citations · 14 across the 18 of their papers we have counts for
5 papers · 1 filter
Krylov Subspace Approximation for Local Community Detection in Large Networks
Kun He, Pan Shi, David Bindel +1
Community detection is an important information mining task to uncover modular structures in large networks. For increasingly common large network data sets, global community detec…
The Local Dimension of Deep Manifold
Mengxiao Zhang, Wangquan Wu, Yanren Zhang +4
Based on our observation that there exists a dramatic drop for the singular values of the fully connected layers or a single feature map of the convolutional layer, and that the di…
Randomness in Deconvolutional Networks for Visual Representation
Kun He, Jingbo Wang, Haochuan Li +5
Toward a deeper understanding on the inner work of deep neural networks, we investigate CNN (convolutional neural network) using DCN (deconvolutional network) and randomization tec…
Snapshot Ensembles: Train 1, get M for free
Gao Huang, Yixuan Li, Geoff Pleiss +3
Ensembles of neural networks are known to be much more robust and accurate than individual networks. However, training multiple deep networks for model averaging is computationally…
Hidden Community Detection in Social Networks
Kun He, Yingru Li, Sucheta Soundarajan +1
We introduce a new paradigm that is important for community detection in the realm of network analysis. Networks contain a set of strong, dominant communities, which interfere with…