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» Robustness and modular structure in networks
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IJIT
2004
14 years 11 months ago
Modeling of Pulping of Sugar Maple Using Advanced Neural Network Learning
This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear un...
W. D. Wan Rosli, Z. Zainuddin, R. Lanouette, S. Sa...
DCOSS
2007
Springer
15 years 3 months ago
Separating the Wheat from the Chaff: Practical Anomaly Detection Schemes in Ecological Applications of Distributed Sensor Networ
Abstract. We develop a practical, distributed algorithm to detect events, identify measurement errors, and infer missing readings in ecological applications of wireless sensor netw...
Luís M. A. Bettencourt, Aric A. Hagberg, Le...
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
15 years 4 months ago
Primal sparse Max-margin Markov networks
Max-margin Markov networks (M3 N) have shown great promise in structured prediction and relational learning. Due to the KKT conditions, the M3 N enjoys dual sparsity. However, the...
Jun Zhu, Eric P. Xing, Bo Zhang
INFOCOM
2009
IEEE
15 years 4 months ago
Fair Routing in Delay Tolerant Networks
—The typical state-of-the-art routing algorithms for delay tolerant networks are based on best next hop hill-climbing heuristics in order to achieve throughput and efficiency. T...
Josep M. Pujol, Alberto Lopez Toledo, Pablo Rodrig...
ADHOC
2007
144views more  ADHOC 2007»
14 years 9 months ago
Adaptive gossip protocols: Managing security and redundancy in dense ad hoc networks
Abstract. Many ad hoc routing algorithms rely on broadcast flooding for location discovery or, more generally, for secure routing applications. Flooding is a robust algorithm but ...
Mike Burmester, Tri Van Le, Alec Yasinsac