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GECCO
2004
Springer
103views Optimization» more  GECCO 2004»
14 years 3 months ago
Training Neural Networks with GA Hybrid Algorithms
Abstract. Training neural networks is a complex task of great importance in the supervised learning field of research. In this work we tackle this problem with five algorithms, a...
Enrique Alba, J. Francisco Chicano
INFOCOM
2007
IEEE
14 years 4 months ago
Low-Complexity Distributed Scheduling Algorithms for Wireless Networks
— We consider the problem of distributed scheduling in wireless networks. We present two different algorithms whose performance is arbitrarily close to that of maximal schedules,...
Abhinav Gupta, Xiaojun Lin, R. Srikant
ICASSP
2009
IEEE
14 years 4 months ago
Time-space-sequential algorithms for distributed Bayesian state estimation in serial sensor networks
We consider distributed estimation of a time-dependent, random state vector based on a generally nonlinear/non-Gaussian state-space model. The current state is sensed by a serial ...
Ondrej Hlinka, Franz Hlawatsch
PERCOM
2009
ACM
14 years 4 months ago
Localizing Jammers in Wireless Networks
Abstract—Wireless communication is susceptible to radio interference and jamming attacks, which prevent the reception of communications. Most existing anti-jamming work does not ...
Hongbo Liu, Wenyuan Xu, Yingying Chen, Zhenhua Liu
IPTPS
2005
Springer
14 years 3 months ago
Locality Prediction for Oblivious Clients
To improve performance, large-scale Internet systems require clients to access nearby servers. While centralized systems can leverage static topology maps for rough network distan...
Kevin P. Shanahan, Michael J. Freedman