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» Digital data networks design using genetic algorithms
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KDD
2004
ACM
196views Data Mining» more  KDD 2004»
14 years 9 months ago
Adversarial classification
Essentially all data mining algorithms assume that the datagenerating process is independent of the data miner's activities. However, in many domains, including spam detectio...
Nilesh N. Dalvi, Pedro Domingos, Mausam, Sumit K. ...
SENSYS
2006
ACM
14 years 2 months ago
Virtual high-resolution for sensor networks
The resolution at which a sensor network collects data is a crucial parameter of performance since it governs the range of applications that are feasible to be developed using tha...
Aman Kansal, William J. Kaiser, Gregory J. Pottie,...
SIGCOMM
1994
ACM
14 years 14 days ago
MACAW: A Media Access Protocol for Wireless LAN's
In recent years, a wide variety of mobile computing devices has emerged, including portables, palmtops, and personal digit al assistants. Providing adequate network connectivity y...
Vaduvur Bharghavan, Alan J. Demers, Scott Shenker,...
GECCO
2008
Springer
117views Optimization» more  GECCO 2008»
13 years 10 months ago
CrossNet: a framework for crossover with network-based chromosomal representations
We propose a new class of crossover operators for genetic algorithms (CrossNet) which use a network-based (or graphbased) chromosomal representation. We designed CrossNet with the...
Forrest Stonedahl, William Rand, Uri Wilensky
SIGIR
2006
ACM
14 years 2 months ago
Large scale semi-supervised linear SVMs
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...
Vikas Sindhwani, S. Sathiya Keerthi