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AI
2002
Springer
15 years 6 months ago
Ensembling neural networks: Many could be better than all
Neural network ensemble is a learning paradigm where many neural networks are jointly used to solve a problem. In this paper, the relationship between the ensemble and its compone...
Zhi-Hua Zhou, Jianxin Wu, Wei Tang
ESA
2005
Springer
108views Algorithms» more  ESA 2005»
16 years 5 days ago
Bootstrapping a Hop-Optimal Network in the Weak Sensor Model
Sensor nodes are very weak computers that get distributed at random on a surface. Once deployed, they must wake up and form a radio network. Sensor network bootstrapping research t...
Martin Farach-Colton, Rohan J. Fernandes, Miguel A...
INFOCOM
2012
IEEE
13 years 9 months ago
SybilDefender: Defend against sybil attacks in large social networks
—Distributed systems without trusted identities are particularly vulnerable to sybil attacks, where an adversary creates multiple bogus identities to compromise the running of th...
Wei Wei, Fengyuan Xu, Chiu Chiang Tan, Qun Li
PODC
2009
ACM
16 years 7 months ago
Coloring unstructured wireless multi-hop networks
We present a randomized coloring algorithm for the unstructured radio network model, a model comprising autonomous nodes, asynchronous wake-up, no collision detection and an unkno...
Johannes Schneider, Roger Wattenhofer
KDD
2010
ACM
250views Data Mining» more  KDD 2010»
15 years 8 months ago
On community outliers and their efficient detection in information networks
Linked or networked data are ubiquitous in many applications. Examples include web data or hypertext documents connected via hyperlinks, social networks or user profiles connected...
Jing Gao, Feng Liang, Wei Fan, Chi Wang, Yizhou Su...