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» Algorithms for Large, Sparse Network Alignment Problems
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ICCAD
2005
IEEE
81views Hardware» more  ICCAD 2005»
15 years 11 months ago
Kauffman networks: analysis and applications
Abstract— A Kauffman network is an abstract model of gene regulatory networks. Each gene is represented by a vertex. An edge from one vertex to another implies that the former ge...
Elena Dubrova, Maxim Teslenko, Andrés Marti...
GECCO
2005
Springer
196views Optimization» more  GECCO 2005»
15 years 7 months ago
Breeding swarms: a new approach to recurrent neural network training
This paper shows that a novel hybrid algorithm, Breeding Swarms, performs equal to, or better than, Genetic Algorithms and Particle Swarm Optimizers when training recurrent neural...
Matthew Settles, Paul Nathan, Terence Soule
121
Voted
PERVASIVE
2007
Springer
15 years 8 months ago
Movement-Based Group Awareness with Wireless Sensor Networks
We propose a method through which dynamic sensor nodes determine that they move together, by communicating and correlating their movement information. We describe two possible solu...
Raluca Marin-Perianu, Mihai Marin-Perianu, Paul J....
KDD
2012
ACM
217views Data Mining» more  KDD 2012»
13 years 4 months ago
Cross-domain collaboration recommendation
Interdisciplinary collaborations have generated huge impact to society. However, it is often hard for researchers to establish such cross-domain collaborations. What are the patte...
Jie Tang, Sen Wu, Jimeng Sun, Hang Su
AI
2007
Springer
15 years 8 months ago
Improving Importance Sampling by Adaptive Split-Rejection Control in Bayesian Networks
Importance sampling-based algorithms are a popular alternative when Bayesian network models are too large or too complex for exact algorithms. However, importance sampling is sensi...
Changhe Yuan, Marek J. Druzdzel